Go Top
Publications
Topics:
- M. M. Bronstein, A. M. Bronstein, Biometrics was no match for hair-raising tricks, Nature Vol. 420, 2002M. M. Bronstein, A. M. Bronstein, M. Zibulevsky, H. Azhari, Reconstruction in ultrasound diffraction tomography using non-uniform FFT, IEEE Trans. on Medical Imaging, Vol. 21(11), 2002 detailsM. M. Bronstein, A. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Iterative reconstruction in diffraction tomography using non-uniform fast Fourier transform, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2002 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Optimal nonlinear estimation of photon coordinates in PET, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2002 details
- A. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Optimal nonlinear line-of-flight estimation in positron emission tomography, IEEE Trans. on Nuclear Science, Vol. 50(3), 2003 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Separation of semireflective layers using Sparse ICA, Proc. Int'l Conf. on Acoustics Speech and Signal Processing (ICASSP), 2003 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression-invariant 3D face recognition, Proc. Audio- and Video-based Biometric Person Authentication (AVBPA), Lecture Notes in Comp. Science No. 2688, Springer, 2003 details
- A. M. Bronstein, M. M. Bronstein, E. Gordon, R. Kimmel, Fusion of 2D and 3D data in three-dimensional face recognition, Proc. Int'l Conf. on Image Processing (ICIP), 2004 detailsM. M. Bronstein, A. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi,, Optimal sparse representations for blind source separation and blind deconvolution: a learning approach, Proc. Int'l Conf. on Image Processing (ICIP), 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Fast relative Newton algorithm for blind deconvolution of images, Proc. Int'l Conf. on Image Processing (ICIP), 2004 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, A. Spira, Face recognition from facial surface metric, Proc. European Conf. on Computer Vision (ECCV), 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Blind source separation using block-coordinate relative Newton method, Signal Processing, Vol. 84(8), 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Blind source separation using the block-coordinate relative Newton method, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, Lecture Notes in Comp. Science No. 3195, Springer, 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, QML blind deconvolution: asymptotic analysis, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Optimal sparse representations for blind deconvolution of images, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Quasi maximum likelihood blind deconvolution of images acquired through scattering media, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2004 details
- A. M. Bronstein, M. M. Bronstein, R. Kimmel, Three-dimensional face recognition, Int'l Journal of Computer Vision (IJCV), Vol. 64(1), 2005 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Quasi maximum likelihood blind deconvolution: super- an sub-Gaussianity versus consistency, IEEE Trans. Signal Processing, Vol. 53(7), 2005 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Relative optimization for blind deconvolution, IEEE Trans. on Signal Processing, Vol. 53(6), 2005 detailsM. M. Bronstein, A. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Blind deconvolution of images using optimal sparse representations, IEEE Trans. on Image Processing, Vol. 14(6), 2005 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression-invariant face recognition via spherical embedding, Proc. Int'l Conf. on Image Processing (ICIP), 2005 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Unmixing tissues: sparse component analysis in multi-contrast MRI, Proc. Int'l Conf. on Image Processing (ICIP), 2005 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Isometric embedding of facial surfaces into S^3, Proc. Int'l Conf. on Scale Space and PDE Methods in Computer Vision (SSVM), 2005 detailsM. M. Bronstein, A. M. Bronstein, R. Kimmel, I. Yavneh, A multigrid approach for multi-dimensional scaling, Proc. Copper Mountain Conf. Multigrid Methods, 2005 (Best Paper Award) detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Sparse ICA for blind separation of transmitted and reflected images, Int'l Journal of Imaging Science and Technology (IJIST), Vol. 15(1), 2005 details
- A. M. Bronstein, M. M. Bronstein, R. Kimmel, Robust expression-invariant face recognition from partially missing data, Proc. European Conf. on Computer Vision (ECCV), 2006 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Matching two-dimensional articulated shapes using generalized multidimensional scaling, Proc. Conf. on Articulated Motion and Deformable Objects (AMDO), 2006 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Face2Face: an isometric model for facial animation, Proc. Conf. on Articulated Motion and Deformable Objects (AMDO), 2006 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Efficient computation of isometry-invariant distances between surfaces, SIAM J. Scientific Computing, Vol. 28(5), 2006A. M. Bronstein, M. M. Bronstein, M. Zibulevsky, On separation of semitransparent dynamic images from static background, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, 2006 detailsM. M. Bronstein, A. M. Bronstein, R. Kimmel, I. Yavneh, Multigrid multidimensional scaling, Numerical Linear Algebra with Applications (NLAA), Vol. 13(2), 2006 (Special issue on multigrid methods) detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Generalized multidimensional scaling: a framework for isometry-invariant partial surface matching, Proc. US National Academy of Sciences (PNAS), Vol. 103(5), 2006 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression invariant face recognition: faces as isometric surfaces, Chapter in Face Processing: Advanced Modeling and Methods (Rama Chellappa, Wenyi Zhao Eds.), Academic Press, 2006 details
- A. M. Bronstein, M. M. Bronstein, R. Kimmel, Calculus of non-rigid surfaces for geometry and texture manipulation, IEEE Trans. Visualization and Computer Graphics, Vol 13(5), 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Rock, Paper, and Scissors: extrinsic vs. intrinsic similarity of non-rigid shapes, Proc. Int'l Conf. Computer Vision (ICCV), 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Weighted distance maps computation on parametric three-dimensional manifolds, Journal of Computational Physics, Vol. 255(1), 2007 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Paretian similarity for partial comparison of non-rigid objects, Proc. Scale Space and Variational Methods in Computer Vision (SSVM), 2007 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Partial similarity of objects and text sequences, Proc. Information Theory and Applications Workshop, 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression-invariant representation of faces, IEEE Trans. Image Processing, Vol. 16(1), 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Story of Cinderella: biometrics and isometry-invariant distances, Chapter in 3D Imaging for Safety and Security (A. Koschan, M. Pollefeys, M. Abidi Eds.), Springer, 2007 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Symmetries of non-rigid shapes, Proc. Workshop on Non-rigid Registration and Tracking through Learning (NRTL), 2007 details
- O. Weber, Y. Devir, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Parallel algorithms for approximation of distance maps on parametric surfaces, ACM Trans. on Graphics, Vol. 27(4), 2008 detailsA. M. Bronstein, M. M. Bronstein, Regularized partial matching of rigid shapes, Proc. European Conf. on Computer Vision (ECCV), 2008 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Analysis of two-dimensional non-rigid shapes, Int'l Journal of Computer Vision (IJCV), Vol. 78(1), 2008 detailsA. M. Bronstein, M. M. Bronstein, Not only size matters: regularized partial matching of nonrigid shapes, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Registration (NORDIA), 2008 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Numerical geometry of non-rigid shapes, Springer, 2008, ISBN: 978-0387733005 detailsG. Rosman, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Topologically constrained isometric embedding, Human Motion Understanding, Modeling, Capture, and Animation, Computational Imaging and Vision, Vol. 36, Springer, 2008 detailsR. Giryes, A. M. Bronstein, Y. Moshe, M. M. Bronstein, Embedded system for 3D shape reconstruction, Proc. European DSP Education and Research Symposium (EDERS), 2008 details
- O. Rubinstein, Y. Honen, A. M. Bronstein, M. M. Bronstein, R. Kimmel, 3D color video camera, Proc. Workshop on 3D Digital Imaging and Modeling (3DIM), 2009 detailsM. Ovsjanikov, A. M. Bronstein, M. M. Bronstein, L. Guibas, ShapeGoogle: a computer vision approach for invariant shape retrieval, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2009 detailsY. Devir, G. Rosman, A. M. Bronstein, M. M. Bronstein, R. Kimmel, On reconstruction of non-rigid shapes with intrinsic regularization, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2009 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Topology-invariant similarity of nonrigid shapes, Int'l Journal of Computer Vision (IJCV), Vol. 81(3), 2009 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Partial similarity of objects, or how to compare a centaur to a horse, Int'l Journal of Computer Vision (IJCV), Vol. 84(2), 2009 detailsA. M. Bronstein, M. M. Bronstein, Y. Carmon, R. Kimmel, Partial similarity of shapes using a statistical significance measure, IPSJ Trans. Computer Vision and Application, Vol. 1, 2009 details
- D. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant geodesic geometry of deformable 3D shapes, arXiv:1012.5936, 2010 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant diffusion geometry for the analysis of deformable 3D shapes, arXiv:1012.5933, 2010 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Full and partial symmetries of non-rigid shapes, Int'l Journal of Computer Vision (IJCV), Vol. 89(1), 2010 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, M. Mahmoudi, G. Sapiro, A Gromov-Hausdorff framework with diffusion geometry for topologically-robust non-rigid shape matching, Int'l Journal of Computer Vision (IJCV), Vol. 89(2), 2010 detailsN. Mitra, A. M. Bronstein, M. M. Bronstein, Intrinsic regularity detection in 3D geometry, Proc. European Conf. Computer Vision (ECCV), 2010 detailsA. M. Bronstein, M. M. Bronstein, Spatially-sensitive affine-invariant image descriptors, Proc. European Conf. Computer Vision (ECCV), 2010 detailsM. M. Bronstein, A. M. Bronstein, F. Michel, N. Paragios, Data fusion through cross-modality metric learning using similarity-sensitive hashing, Proc. Computer Vision and Pattern Recognition (CVPR), 2010 detailsD. Raviv, M. M. Bronstein, A. M. Bronstein, R. Kimmel, Volumetric heat kernel signatures, Proc. Int'l Workshop on 3D Object Retrieval (3DOR), ACM Multimedia, 2010 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, G. Sapiro, Diffusion symmetries of non-rigid shapes, Proc. Int'l Symposium on 3D Data Processing, Visualization and Transmission (3DPVT), 2010 detailsG. Rosman, M. M. Bronstein, A. M. Bronstein, R. Kimmel, Nonlinear dimensionality reduction by topologically constrained isometric embedding, Intl. Journal of Computer Vision (IJCV), Vol. 89(1), 2010 detailsA. M. Bronstein, M. M. Bronstein, U. Castellani, B. Falcidieno, A. Fusiello, A. Godil, L. J. Guibas, I. Kokkinos, Z. Lian, M. Ovsjanikov, G. Patané, M. Spagnuolo, R. Toldo, SHREC 2010: robust large-scale shape retrieval benchmark, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2010 detailsA. M. Bronstein, M. M. Bronstein, B. Bustos, U. Castellani, M. Crisani, B. Falcidieno, L. J. Guibas, I. Kokkinos, V. Murino, M. Ovsjanikov, G. Patané, I. Sipiran, M. Spagnuolo, J. Sun, SHREC 2010: robust feature detection and description benchmark, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2010 detailsA. M. Bronstein, M. M. Bronstein, U. Castellani, A. Dubrovina, L. J. Guibas, R. P. Horaud, R. Kimmel, D. Knossow, E. von Lavante, D. Mateus, M. Ovsjanikov, A. Sharma, SHREC 2010: robust correspondence benchmark, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2010 details
- R. Kimmel, C. Zhang, A. M. Bronstein, M. M. Bronstein, Are MSER features really interesting?, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 33(11), 2011 detailsA. M. Bronstein, Spectral descriptors for deformable shapes, arXiv:1110.5015, 2011 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant diffusion geometry for the analysis of deformable 3D shapes, Proc. Computer Vision and Pattern Recognition (CVPR), 2011 detailsM. M. Bronstein, A. M. Bronstein, Shape recognition with spectral distances, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 33(5), 2011 detailsJ. Pokrass, A. M. Bronstein, M. M. Bronstein, A correspondence-less approach to matching of deformable shapes, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsA. Kovnatsky, M. M. Bronstein, A. M. Bronstein, R. Kimmel, Photometric heat kernel signatures, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsJ. Aflalo, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Deformable shape retrieval by learning diffusion kernels, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsG. Rosman, M. M. Bronstein, A. M. Bronstein, A. Wolf, R. Kimmel, Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsC. Wang, M. M. Bronstein, A. M. Bronstein, N. Paragios, Discrete minimum distortion correspondence problems for non-rigid shape matching, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsA. Hooda, M. M. Bronstein, A. M. Bronstein, R. Horaud, Shape palindromes: analysis of intrinsic symmetries in 2D articulated shapes, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsF. Michel, M. M. Bronstein, A. M. Bronstein, N. Paragios, Boosted metric learning for 3D multi-modal deformable registration, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2011 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant geodesic geometry of deformable 3D shapes, Computers and Graphics (CAG), Vol. 35(3), 2011 detailsR. Litman, A. M. Bronstein, A. M. Bronstein, Diffusion-geometric maximally stable component detection in deformable shapes, Computers and Graphics (CAG), Vol. 35(3), 2011 detailsA. M. Bronstein, M. M. Bronstein, M. Ovsjanikov, L. J. Guibas, Shape Google: geometric words and expressions for invariant shape retrieval, ACM Trans. Graphics (TOG), Vol. 30(1), 2011 detailsA. M. Bronstein, M. M. Bronstein, Metric approaches to invariant shape similarity, Chapter in Handbook of Mathematical Methods in Imaging (O. Scherzer Ed.), Springer, 2011 details
- P. Sprechmann, A. M. Bronstein, G. Sapiro, Real-time online singing voice separation from monaural recordings using robust low-rank modeling, Proc. Annual Conference of the Int'l Society for Music Information Retrieval (ISMIR), 2012 (Best poster presentation award) detailsO. Litany, A. M. Bronstein, M. M. Bronstein, Putting the pieces together: regularized multi-shape partial matching, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012 detailsA. Kovnatsky, A. M. Bronstein, M. M. Bronstein, Stable spectral mesh filtering, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012 detailsI. Kokkinos, M. M. Bronstein, R. Litman, A. M. Bronstein, Intrinsic shape context descriptors for deformable shapes, Proc. Computer Vision and Pattern Recognition (CVPR), 2012 detailsE. Rodolà, A. M. Bronstein, A. Albarelli, F. Bergamasco, A. Torsello, A game-theoretic approach to deformable shape matching, Proc. Computer Vision and Pattern Recognition (CVPR), 2012 detailsM. Spagnuolo, M. M. Bronstein, A. M. Bronstein, A. Ferreira (Eds.), Eurographics Workshop on 3D Object Retrieval, Eurographics Association, 2012, ISBN: 978-3-905674-36-1 detailsR. Litman, A. M. Bronstein, M. M. Bronstein, Stable volumetric features in deformable shapes, Computers and Graphics (CAG), Vol. 36(5), 2012 detailsG. Rosman, A. M. Bronstein, M. M. Bronstein, X.-C. Tai, R. Kimmel, Group-valued regularization for analysis of articulated motion, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Learning efficient structured sparse models, Proc. Int'l Conf. on Machine Learning (ICML), 2012 detailsA. Zabatani, A. M. Bronstein, Parallelized algorithms for rigid surface alignment on GPU, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2012 detailsG. Rosman, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Articulated motion segmentation of point clouds by group-valued regularization, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2012 detailsA. Kovnatsky, M. M. Bronstein, A. M. Bronstein, D. Raviv, R. Kimmel, Affine-invariant photometric heat kernel signatures, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2012 detailsC. Strecha, A. M. Bronstein, M. M. Bronstein, P. Fua, LDAHash: improved matching with smaller descriptors, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 34(1), 2012 detailsB. M. Bruckstein, B. ter haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.), Scale Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science (LNCS) No. 6667, Springer, 2012, ISBN: 978-3-642-24784-2 detailsR. Litman, A. M. Bronstein, M. M. Bronstein, Stable semi-local features for non-rigid shapes, Chapter in Innovations for Shape Analysis: Models and Algorithms (M. Breuss, A. M. Bruckstein, P. Maragos Eds.), Springer, 2012 detailsG. Rosman, M. M. Bronstein, A. M. Bronstein, A. Wolf, R. Kimmel, Group-valued regularization for motion segmentation of articulated shapes, Chapter in Innovations for Shape Analysis: Models and Algorithms (M. Breuss, A. M. Bruckstein, P. Maragos Eds.), Springer, 2012 detailsA. M. Bronstein, M. M. Bronstein, M. Ovsjanikov, 3D features, surface descriptors, and object descriptors, Chapter in 3D Imaging, Analysis and Applications (N. Pears, Y. Liu, P. Bunting, Eds.), Springer, 2012. details
- P. Sprechmann, R. Litman, T. Ben Yakar, A. M. Bronstein, G. Sapiro, Efficient supervised sparse analysis and synthesis operators, Proc. Neural Information Proc. Systems (NIPS), 2013 detailsT. Ben Yakar, R. Litman, P. Sprechmann, A. M. Bronstein, G. Sapiro, Bilevel sparse models for polyphonic music transcription, Proc. Annual Conf. of the Int'l Society for Music Info. Retrieval (ISMIR), 2013 detailsJ. Pokrass, A. M. Bronstein, M. M. Bronstein, P. Sprechmann, G. Sapiro, Sparse modeling of intrinsic correspondences, Computer Graphics Forum (CGF), Vol. 32(2), 2013 detailsA. Kovnatsky, M. M. Bronstein, A. M. Bronstein, K. Glashoff, R. Kimmel, Coupled quasi-harmonic bases, Computer Graphics Forum (CGF), Vol. 32(2), 2013 detailsP. Sprechmann, A. M. Bronstein, J.-M. Morel, G. Sapiro, Audio restoration from multiple copies, Proc. Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2013 detailsP. Sprechmann, A. M. Bronstein, M. M. Bronstein, G. Sapiro, Learnable low rank sparse models for speech denoising, Proc. Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2013 detailsA. Kovnatski, D. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Geometric and photometric data fusion in non-rigid shape analysis, Numerical Mathematics: Theory, Methods and Applications (NM-TMA), Vol. 6(1), 2013 detailsJ. Pokrass, A. M. Bronstein, M. M. Bronstein, Partial shape matching without point-wise correspondence, Numerical Mathematics: Theory, Methods and Applications (NM-TMA), Vol. 6(1), 2013 detailsR. Litman, and A. M. Bronstein, Learning spectral descriptors for deformable shape correspondence, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 36(1), 2013 details
- Q. Qiu, G. Sapiro, A. M. Bronstein, Random forests can hash, arXiv:1412.5083, 2014 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Supervised non-Euclidean sparse NMF via bilevel optimization with applications to speech enhancement, Proc. Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA), 2014 detailsS. Korman, R. Litman, S. Avidan, A. M. Bronstein, Probably approximately symmetric: Fast rigid symmetry detection with global guarantees, Computer Graphics Forum (CGF), Vol. 34(1), 2014 detailsR. Litman, A. M. Bronstein, M. M. Bronstein, U. Castellani, Supervised learning of bag-of-features shape descriptors using sparse coding, Computer Graphics Forum (CGF), Vol. 33(5), 2014 detailsO. Menashe, A. M. Bronstein, Real-time compressed imaging of scattering volumes, Proc. Int'l Conf. on Image Processing (ICIP), 2014 detailsS. Biasotti, A. Cerri, A. M. Bronstein, M. M. Bronstein, Quantifying 3D shape similarity using maps: Recent trends, applications and perspectives, Proc. EUROGRAPHICS STARS, 2014 detailsJ. Masci, M. M. Bronstein, A. M. Bronstein, J. Schmidhuber, Multimodal similarity-preserving hashing, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 36(4), 2014 detailsJ. Masci, A. M. Bronstein, M. M. Bronstein, P. Sprechmann, G. Sapiro, Sparse similarity-preserving hashing, Proc. Int'l Conf. on Learning Representations (ICLR), 2014 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Equi-affine invariant intrinsic geometries for bendable shapes analysis, Journal of Mathematical Imaging and Vision (JMIV), Vol. 50(1), 2014 detailsD. Pickup, X. Sun, P. L. Rosin, R. R. Martin, Z. Cheng, Z. Lian, M. Aono, A. Ben Hamza, A. M. Bronstein, M. M. Bronstein, S. Bu, U. Castellani, S. Cheng, V. Garro, A. Giachetti, A. Godil, J. Han, H. Johan, L. Lai, B. Li, C. Li, H. Li, R. Litman, X. Liu, Z. Liu, Y. Lu, A. Tatsuma, J. Ye, Shape retrieval of non-rigid 3D human models, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2014 details
- O. Litany, T. Remez, A. M. Bronstein, Image reconstruction from dense binary pixels, arXiv:1512.01774, 2015D. Eynard, A. Kovnatsky, M. M. Bronstein, K. Glashoff, A. M. Bronstein, Multimodal manifold analysis using simultaneous diagonalization of Laplacians, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 37(12), 2015 detailsT. Remez, O. Litany, A. M. Bronstein, A Picture is Worth a Billion Bits: Real-time image reconstruction from dense binary pixels, arXiv:1510.04601, 2015 detailsA. M. Bronstein, New dimensions of media, Universidad La Salle, Revista de ciencias de la computación, Vol. 3(1), 2015H. Haim, A. M. Bronstein, E. Marom, Computational all-in-focus imaging using an optical phase mask, OSA Optics Express, Vol. 23(19), 2015 detailsR. Litman, S. Korman, A. M. Bronstein, S. Avidan, GMD: Global model detection via inlier rate estimation, Proc. Computer Vision and Pattern Recognition (CVPR), 2015 detailsI. Sipiran, B. Bustos, T. Schreck, A. M. Bronstein, M. M. Bronstein, U. Castellani, S. Choi, L. Lai, H. Li, R. Litman, L. Sun, SHREC'15 Track: Scalability of non-rigid 3D shape retrieval, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2015 detailsX. Bian, H. Krim, A. M. Bronstein, L. Dai, Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis, Proc. Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2015 detailsY. Aflalo, A. M. Bronstein, R. Kimmel, On convex relaxation of graph isomorphism, Proc. US National Academy of Sciences (PNAS), 2015 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Learning efficient sparse and low-rank models, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 37(9), 2015 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Supervised non-negative matrix factorization for audio source separation, Chapter in Excursions in Harmonic Analysis (R. Balan, M. Begue, J. J. Benedetto, W. Czaja, K. Okoudjou Eds.), Birkhaeuser, 2015 details
- Y. Choukroun, A. Shtern, A. M. Bronstein, R. Kimmel, Hamiltonian operator for spectral shape analysis, arXiv:1611.01990, 2016 detailsA. M. Bronstein, Y. Choukroun, R. Kimmel, M. Sela, Consistent discretization and minimization of the L1 norm on manifolds, Proc. 3D Vision (3DV), 2016 detailsR. Litman, A. M. Bronstein, SpectroMeter: Amortized sublinear spectral approximation of distance on graphs, Proc. 3D Vision (3DV), 2016 detailsT. Remez, O. Litany, S. Yoseff, H. Haim, A. M. Bronstein, FPGA system for real-time computational extended depth of field imaging using phase aperture coding, arXiv:1608.01074, 2016 detailsR. Giryes, G. Sapiro, A. M. Bronstein, Deep neural networks with random Gaussian weights: A universal classification strategy?, IEEE Trans. Signal Processing, Vol. 64(13), 2016 detailsO. Litany, E. Rodolà, A. M. Bronstein, M. M. Bronstein, D. Cremers, Non-rigid puzzles, Computer Graphics Forum, Vol. 35(5), 2016 (SGP Best Paper Award) detailsX. Bian, H. Krim, A. M. Bronstein, L. Dai, Sparsity and nullity: paradigms for analysis dictionary learning, SIAM J. Imaging Sci., Vol. 9(3), 2016 detailsD. Pickup, X. Sun, P. L. Rosin, R. R. Martin, Z. Cheng, Z. Lian, M. Aono, A. Ben Hamza, A. M. Bronstein, M. M. Bronstein, S. Bu, U. Castellani, S. Cheng, V. Garro, A. Giachetti, A. Godil, J. Han, H. Johan, L. Lai, B. Li, C. Li, H. Li, R. Litman, X. Liu, Z. Liu, Y. Lu, A. Tatsuma, J. Ye, Shape retrieval of non-rigid 3D human models, Intl. Journal of Computer Vision (IJCV), 2016 details
- S. Vedula, O. Senouf, A. M. Bronstein, O. V. Michailovich, M. Zibulevsky, Towards CT-quality ultrasound imaging using deep learning, arXiv:1710.06304, 2017 detailsO. Litany, T. Remez, E. Rodolà, A. M. Bronstein, M. M. Bronstein, Deep Functional Maps: Structured prediction for dense shape correspondence, Proc. Int'l Conf. on Computer Vision (ICCV), 2017 detailsZ. Laehner, M. Vestner, A. Boyarski, O. Litany, R. Slossberg, T. Remez, E. Rodolà, A. M. Bronstein, M. M. Bronstein, R. Kimmel, D. Cremers, Efficient deformable shape correspondence via kernel matching, Proc. 3D Vision (3DV), 2017 detailsG. Alexandroni, Y. Podolsky, H. Greenspan, T. Remez, O. Litany, A. M. Bronstein, R. Giryes, White matter fiber representation using continuous dictionary learning, Proc. Int'l Conf. Medical Image Computing & Computer Assisted Intervention (MICCAI), 2017 detailsM. Vestner, R. Litman, E. Rodolà, A. M. Bronstein, D. Cremers, Product Manifold Filter: Non-rigid shape correspondence via kernel density estimation in the product space, Proc. Computer Vision and Pattern Recognition (CVPR), 2017 detailsO. Litany, E. Rodolà, A. M. Bronstein, M. M. Bronstein, Fully spectral partial shape matching, Computer Graphics Forum, Vol. 36(2), 2017 detailsA. Boyarski, A. M. Bronstein, M. M. Bronstein, Subspace least squares multidimensional scaling, Proc. Scale Space and Variational Methods (SSVM), 2017 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Deep class-aware image denoising, Proc. Int'l Conf. on Image Processing (ICIP), 2017 detailsO. Litany, T. Remez, A. M. Bronstein, Cloud Dictionary: Sparse coding and modeling for point clouds, arXiv:1612.04956, 2017 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Deep class-aware denoising, arXiv:1701.01698, 2017 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Deep convolutional denoising of low-light images, arXiv:1701.01687, 2017 detailsO. Litany, T. Remez, D. Freedman, L. Shapira, A. M. Bronstein, R. Gal, ASIST: Automatic Semantically Invariant Scene Transformation, Computer Vision and Image Understanding, Vol. 157, 2017 detailsM. Ovsjanikov, E. Corman, M. M. Bronstein, E. Rodolà, M. Ben-Chen, L. Guibas, F. Chazal, A. M. Bronstein, Computing and processing correspondences with functional maps, SIGGRAPH Courses, 2017 details
- E. Schwartz, L. Karlinsky, J. Shtok, S. Harary, M. Marder, R. Feris, A. Kumar, R. Giryes, A. M. Bronstein, ∆-encoder: an effective sample synthesis method for few-shot object recognition, Proc. Neural Information Processing Systems (NIPS), 2018 detailsE. Rodolà, Z. Lähner, A. M. Bronstein, M. M. Bronstein, J. Solomon, Functional maps representation on product manifolds, arXiv:1809.10940, 2018 detailsC. Baskin, N. Liss, Y. Chai, E. Zheltonozhskii, E. Schwartz, R. Giryes, A. Mendelson, A. M. Bronstein, NICE: noise injection and clamping estimation for neural network quantization, arXiv:1810.00162, 2018 detailsQ. Qiu, J. Lezama, A. M. Bronstein, G. Sapiro, ForestHash: Semantic hashing with shallow random forests and tiny convolutional networks, Proc. European Conf. on Computer Vision (ECCV), 2018 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Class-aware fully-convolutional Gaussian and Poisson denoising, IEEE Trans. Image Processing, Vol. 27(11), 2018 detailsA. Tsitsulin, D. Mottin, P. Karras, A. M. Bronstein, E, Mueller, NetLSD: Hearing the shape of a graph, Proc. ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), 2018 detailsO. Senouf, S. Vedula, G. Zurakhov, A. M. Bronstein, M. Zibulevsky, O. Michailovich, D. Adam, D. Blondheim, High frame-rate cardiac ultrasound imaging with deep learning, Proc. Int'l Conf. Medical Image Computing & Computer Assisted Intervention (MICCAI), 2018 detailsS. Vedula, O. Senouf, G. Zurakhov, A. M. Bronstein, M. Zibulevsky, O. Michailovich, D. Adam, D. Gaitini, High quality ultrasonic multi-line transmission through deep learning, Proc. Machine Learning for Medical Image Reconstruction (MLMIR), 2018 detailsA. Tsitsulin, D. Mottin, P. Karras, A. M. Bronstein, E, Mueller, SGR: Self-supervised spectral graph representation learning, Proc. KDD Deep Learning Day, 2018 detailsE. Schwartz, R. Giryes, A. M. Bronstein, DeepISP: Towards learning an end-to-end image processing pipeline, IEEE Trans. on Image Processing, 2018 detailsH. Haim, S. Elmalem, R. Giryes, A. M. Bronstein, E. Marom, Depth estimation from a single image using deep learned phase coded mask, IEEE Trans. Computational Imaging, Vol. 2(3), 2018 (Winner of the OSA Student Grand Challenge The Optical System of the Future) detailsE. Tsitsin, A. M. Bronstein, T. Hendler, M. Medvedovsky, Passive electric impedance tomography, Proc. Electric Impedance Tomography (EIT), 2018 detailsE. Tsitsin, T. Mund, A. M. Bronstein, Printable anisotropic phantom for EEG with distributed current sources, Proc. IEEE Int'l Symposium on Biomedical Imaging (ISBI), 2018 detailsE. Tsitsin, M. Medvedovsky, A. M. Bronstein, VibroEEG: Improved EEG source reconstruction by combined acoustic-electric imaging, Proc. IEEE Int'l Symposium on Biomedical Imaging (ISBI), 2018 detailsC. Baskin, N. Liss, E. Zheltonozhskii, A. M. Bronstein, A. Mendelson, Streaming architectures for large-scale quantized neural networks on an FPGA-based dataflow platform, IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2018 detailsR. Giryes, Y. C. Eldar, A. M. Bronstein, G. Sapiro, Tradeoffs between convergence speed and reconstruction accuracy in inverse problems, IEEE Trans. on Signal Processing, Vol. 66(7), 2018 details
- A. Boyarski, S. Vedula, A. M. Bronstein, Deep matrix factorization with spectral geometric regularization, arXiv: 1911.07255, 2019 detailsY. Nahshan, B. Chmiel, C. Baskin, E. Zheltonozhskii, R. Banner, A. M. Bronstein, A. Mendelson, Loss aware post-training quantization, arXiv: 1911.07190, 2019 detailsY. Nemcovsky, E. Zheltonozhskii, C. Baskin, B. Chmiel, A. M. Bronstein, A. Mendelson, Smoothed inference for adversarially-trained models, arXiv: 1911.07198, 2019 detailsS. Doveh, E. Schwartz, C. Xue, R. Feris, A. M. Bronstein, R. Giryes, L. Karlinsky, MetAdapt: Meta-learned task-adaptive architecture for few-shot classification, arXiv: 1912.00412, 2019 detailsE. Rozenberg, D. Freedman, A. M. Bronstein, Localization with limited annotation for chest X-rays, Proc. ML4H, NeurIPS, 2019 detailsS. Vedula, O. Senouf, G. Zurakov, A. M. Bronstein, O. Michailovich, M. Zibulevsky, Learning beamforming in ultrasound imaging, Proc. Medical Imaging with Deep Learning (MIDL), 2019 detailsE. Schwartz, L. Karlinsky, J. Shtok, S. Harary, M. Marder, R. Feris, A. Kumar, R. Giryes, A. M. Bronstein, RepMet: Representative-based metric learning for classification and one-shot object detection, Proc. Computer Vision and Pattern Recognition (CVPR), 2019 detailsO. Halimi, O. Litany, E. Rodolà, A. M. Bronstein, R. Kimmel, Self-supervised learning of dense shape correspondence, Proc. Computer Vision and Pattern Recognition (CVPR), 2019 detailsA. Alfassy, L. Karlinsky, A. Aides, J. Shtok, S. Harary, R. Feris, R. Giryes, A. M. Bronstein, LaSO: Label-Set Operations networks for multi-label few-shot learning, Proc. Computer Vision and Pattern Recognition (CVPR), 2019 detailsA. Zabatani, V. Surazhsky, E. Sperling, S. Ben Moshe, O. Menashe, D. H. Silver, Z. Karni, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Intel RealSense SR300 Coded light depth Camera, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), 2019 detailsY. Zur, C. Baskin, E. Zheltonozhskii, B. Chmiel, I. Evron, A. M. Bronstein, A. Mendelson, Towards learning of filter-level heterogeneous compression of convolutional neural networks, Proc. AutoML Workshop, Int'l Conf. on Machine Learning (ICML), 2019 detailsE. Schwartz, L. Karlinsky, R. Feris, R. Giryes, A. M. Bronstein, Baby steps towards few-shot learning with multiple semantics, arXiv:1906.01905, 2019 detailsA. Rampini, I. Tallini, M. Ovsjanikov, A. M. Bronstein, E. Rodola, Correspondence-free region localization for partial shape similarity via Hamiltonian spectrum alignment, Proc. 3D Vision (3DV), 2019 (Best paper award) detailsO. Senouf, S. Vedula, T. Weiss, A. M. Bronstein, O. Michailovich, M. Zibulevsky, Self-supervised learning of inverse problem solvers in medical imaging, Proc. Medical Image Learning with Less Labels and Imperfect Data, MICCAI 2019 detailsR. M. Dyke, C Stride, Y.-K. Lai, P. L. Rosin, M. Aubry, A. Boyarski, A. M. Bronstein, M. M. Bronstein, D. Cremers, M. Fisher, T. Groueix, D. Guo, V. G. Kim, R. Kimmel, Z. Lähner, K. Li, O. Litany, T. Remez, E. Rodolà, B. C. Russell, Y. Sahillioglu, R. Slossberg, M. Vestner, Z. Wu, J. Yang, Gary Tam, Shape Correspondence with Isometric and Non-Isometric Deformations, Eurographics Workshop on 3D Object Retrieval, 2019 detailsN. Diamant, D. Zadok, C. Baskin, E. Schwartz, A. M. Bronstein, Beholder-GAN: Generation and beautification of facial images with conditioning on their beauty level, Proc. Int'l Conf. on Image Processing (ICIP), 2019 detailsG. Pai, R. Talmon, A. M. Bronstein, R. Kimmel, DIMAL: Deep isometric manifold learning using sparse geodesic sampling, Proc. IEEE Winter Conf. on Applications of Computer Vision (WACV), 2019 detailsO. Litany, E. Rodolà, A. M. Bronstein, M. M. Bronstein, D. Cremers, Partial single- and multi-shape dense correspondence using functional maps, Chapter in The Handbook of Numerical Analysis - Processing, Analyzing and Learning of Images, Shapes, and Forms, Elsevier, 2019 detailsA. Boyarski, A. M. Bronstein, Multidimensional scaling, Computer Vision: A Reference Guide, (Katsushi Ikeuchi, Ed.) details
- C. Baskin, E. Schwartz, E. Zheltonozhskii, N. Liss, R. Giryes, A. M. Bronstein, A. Mendelson, UNIQ: Uniform noise injection for non-uniform quantization of neural networks, ACM Transactions on Computer Systems (TOCS), 2020 detailsB. Finkelshtein, C. Baskin, E. Zheltonozhskii, U. Alon, Single-node attack for fooling graph neural networks, arXiv:2011.03574, 2020 detailsJ. Alush-Aben, L. Ackerman-Schraier, T. Weiss, S. Vedula, O. Senouf, A. M. Bronstein, 3D FLAT: Feasible Learned Acquisition Trajectories for Accelerated MRI, Proc. Machine Learning for Medical Image Reconstruction, MICCAI 2020 detailsT. Weiss, S. Vedula, O. Senouf, O. Michailovich, A. M. Bronstein, Towards learned optimal q-space sampling in diffusion MRI, Proc. Computational Diffusion MRI, MICCAI 2020 detailsE. Zheltonozhskii, C. Baskin, A. M. Bronstein, A. Mendelson, Self-supervised learning for large-scale unsupervised image clustering, NeurIPS 2020 Workshop: Self-Supervised Learning - Theory and Practice, 2020 detailsG. Mariani, L. Cosmo, A. M. Bronstein, E. Rodolà, Generating adversarial surfaces via band-limited perturbations, Computer Graphics Forum, 2020 detailsB. Chmiel, C. Baskin, R. Banner, E. Zheltonozshkii, Y. Yermolin, A. Karbachevsky, A. M. Bronstein, A. Mendelson, Feature map transform coding for energy-efficient CNN inference, Proc. Intl. Joint Conf. on Neural Networks (IJCNN), 2020 detailsE. Amrani, R. Ben-Ari, T. Hakim, A. M. Bronstein, Self-Supervised Object Detection and Retrieval Using Unlabeled Videos, CVPR workshop, 2020 detailsD. H. Silver, M. Feder, Y. Gold-Zamir, A. L. Polsky, S. Rosentraub, E. Shachor, A. Weinberger, P. Mazur, V. D. Zukin, A. M. Bronstein, Data-driven prediction of embryo implantation probability using IVF time-lapse imaging, Proc. MIDL, 2020 detailsT. Weiss, S. Vedula, O. Senouf, A. M. Bronstein, O. Michailovich, M. Zibulevsky, Joint learning of Cartesian undersampling and reconstruction for accelerated MRI, Proc. Int’l Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2020 detailsS. Sommer, A. M. Bronstein, Horizontal flows and manifold stochastics in geometric deep learning, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), 2020 detailsK. Rotker, D. Ben-Bashat, A. M. Bronstein, Over-parameterized models for vector fields, SIAM Journal on Imaging Sciences (SIIMS), 2020 detailsA. Tsitsulin, M. Munkhoeva, D. Mottin, P. Karras. A. M. Bronstein, I. Oseledets, E. Müller, Intrinsic multi-scale evaluation of generative models, Proc. ICLR, 2020 detailsA. Karbachevsky, C. Baskin, E. Zheltonozshkii, Y. Yermolin, F. Gabbay, A. M. Bronstein, A. Mendelson, HCM: Hardware-aware complexity metric for neural network architectures, arXiv:2004.08906, 2020 detailsE. Zheltonozhskii, C. Baskin, Y. Nemcovsky, B. Chmiel, A. Mendelson, A. M. Bronstein, Colored noise injection for training adversarially robust neural networks, arXiv:2003.02188, 2020 detailsA. Livne, A. M. Bronstein, R. Kimmel, Z. Aviv, S. Grofit, Do we need depth in state-of-the-art face authentication?, Proc. IEEE Int'l Conf. on 3D Vision (3DV), 2020 detailsM. Shkolnik, B. Chmiel, R. Banner, G. Shomron, Y. Nahshan, A. M. Bronstein, U. Weiser, Robust Quantization: One Model to Rule Them All, Proc. NeurIPS, 2020 detailsY. Choukroun , A. Shtern, A. M. Bronstein, R. Kimmel, Hamiltonian operator for spectral shape analysis, IEEE Trans. Vis. and Comp. Graphics, vol. 26(2), 2020 details
- A. Arbelle, S. Doveh, A. Alfassy, J. Shtok, G. Lev, E. Schwartz, H. Kuehne, H. Barak Levi, P. Sattigeri, R. Panda, C.-F. Chen, A. M. Bronstein, K. Saenko, S. Ullman, R. Giryes, R. Feris, L. Karlinsky, Detector-free weakly supervised grounding by separation, Proc. CVPR, 2022 detailsS. Doveh, E. Schwartz, C. Xue, R. Feris, A. M. Bronstein, R. Giryes, L. Karlinsky, MetAdapt: Meta-learned task-adaptive architecture for few-shot classification, Pattern Recognition Letters, 2021 detailsT. Weiss, N. Peretz, S. Vedula, A. Feuer, A. M. Bronstein, Joint optimization of system design and reconstruction in MIMO radar imaging, Proc. IEEE Int'l Workshop on Machine Learning for Signal Processing, 2021 detailsY. Nahshan, B. Chmiel, C. Baskin, E. Zheltonozhskii, R. Banner, A. M. Bronstein, A. Mendelson, Loss aware post-training quantization, Machine Learning, 2021 detailsC. Baskin, B. Chmiel, E. Zheltonozhskii, R. Banner, A. M. Bronstein, A. Mendelson, CAT: Compression-aware training for bandwidth reduction, JMLR, 2021 detailsE. Rozenberg, D. Freedman, A. M. Bronstein, Learning to localize objects using limited annotation with applications to thoracic diseases, IEEE Access Vol. 9, 2021 detailsT. Weiss, O. Senouf, S. Vedula, O. Michailovich, M. Zibulevsky, A. M. Bronstein, PILOT: Physics-Informed Learned Optimal Trajectories for accelerated MRI, Journal of Machine Learning for Biomedical Imaging (MELBA), 2021 detailsY. Elul, A. Rosenberg, A. Schuster, A. M. Bronstein, Y. Yaniv, Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis, Proc. US National Academy of Sciences (PNAS), 2021 detailsL. Karlinsky, J. Shtok, A. Alfassy, M. Lichtenstein, S. Harary, E. Schwartz, S. Doveh, P. Sattigeri, R. Feris, A. M. Bronstein, R. Giryes, StarNet: towards weakly supervised few-shot detection and explainable few-shot classification, Proc. AAAI, 2021 detailsE. Amrani, R. Ben-Ari, D. Rotman, A. M. Bronstein, Noise estimation using density estimation for self-supervised multimodal learning, Proc. AAAI, 2021 detailsO. Dahary, M. Jacoby, A. M. Bronstein, Digital Gimbal: End-to-end deep image stabilization with learnable exposure times, Proc. CVPR, 2021 detailsA. Boyarski, S. Vedula, A. M. Bronstein, Spectral geometric matrix completion, Proc. Mathematical and Scientific Machine Learning, 2021 detailsE. Rozenberg, A. Karnieli, O. Yesharim, S. Trajtenberg-Mills, D. Freedman, A. M. Bronstein, A. Arie, Inverse design of quantum holograms in three-dimensional nonlinear photonic crystals, CLEO, 2021 detailsA. Karbachevsky, C. Baskin, E. Zheltonozshkii, Y. Yermolin, F. Gabbay, A. M. Bronstein, A. Mendelson, Early-stage neural network hardware performance analysis, Sustainability 13(2):717, 2021 details
- J. Hermanns, A. Tsitsulin, M. Munkhoeva, A. M. Bronstein, D. Mottin, P. Karras, GRASP: Graph Alignment through Spectral Signatures, Proc. Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data, 2022 detailsP. Kang, Z. Lin, Z. Yang, A. M. Bronstein, Q. Li, W. Liu, Deep fused two-step cross-modal hashing with multiple semantic supervision, Multimedia Tools and Applications, 2022 detailsP. Kang, Z. Lin, Z. Yang, X. Fang, A. M. Bronstein, Q. Li, W. Liu, Intra-class low-rank regularization for supervised and semi-supervised cross-modal retrieval, Applied Intelligence, 52(1), pp. 33-54, 2022 detailsY. Nemcovsky, M. Jacoby, A. M. Bronstein, C. Baskin, Physical passive patch adversarial attacks on visual odometry systems, Proc. ACCV, 2022 detailsL. Ackerman-Schraier, A. A. Rosenberg, A. Marx, A. M. Bronstein, Machine learning approaches demonstrate that protein structures carry information about their genetic coding, Nature Scientific Reports, 2022 detailsA. A. Rosenberg, N. Yehishalom, A. Marx, A. M. Bronstein, Defining amino acid pairs as structural units suggests mutation sensitivity to adjacent residues, biorXiv/2022/513383, 2022 detailsA. Rosenberg, A. Marx, A. M. Bronstein, Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon, Nature Communications, 2022 detailsE. Rozenberg, A. Karnieli, O. Yesharim, J. Foley-Comer, S. Trajtenberg-Mills, D. Freedman, A. M. Bronstein, A. Arie, Inverse design of spontaneous parametric downconversion for generation of high-dimensional qudits, Optica 9, 602-615, 2022 detailsN. Talati, H. Ye, S. Vedula, K.-Y. Chen, Y. Chen, D. Liu, Y. Yuan, D. Blaauw, A. M. Bronstein, T. Mudge, R. Dreslinski, Mint: An Accelerator For Mining Temporal Motifs, Proc. MICRO, 2022 detailsE. Zheltonozhskii, C. Baskin, A. Mendelson, A. M. Bronstein, O. Litany, Contrast to divide: Self-supervised pre-training for learning with noisy labels, Proc. of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022 detailsG. Pai, A. Bronstein, R. Talmon, R. Kimmel, Deep isometric maps, Image and Vision Computing, 2022 detailsN. Diamant, N. Shandor, A. M. Bronstein, Delta-GAN-Encoder: Encoding semantic changes for explicit image editing, using few synthetic samples, arXiv:2111.08419, 2022 detailsT. Blau, R. Ganz, B. Kawar, A. M. Bronstein, M. Elad , Threat model-agnostic adversarial defense using diffusion models, arXiv preprint arXiv:2207.08089, 2022 detailsD. E. Fordham, D. Rosentraub, A. L. Polsky, T. Aviram, Y. Wolf, O. Perl, A. Devir, S. Rosentraub, D. H. Silver, Y. Gold Zamir, A. M. Bronstein, M. Lara Lara, J. Ben Nagi, A. Alvarez, S. Munné, Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity?, Human Reproduction, Volume 37, Issue 10, Pages 2275–2290, 2022 detailsE. Amrani, A. M. Bronstein, Self-supervised classification network, Proc. ECCV, 2022 details
- A. A. Rosenberg, N. Yehishalom, A. Marx, A. M. Bronstein, An amino-domino model described by a cross-peptide-bond Ramachandran plot defines amino acid pairs as local structural units, Proc. US National Academy of Sciences (PNAS), 2023 detailsT. Weiss, L. Cosmo, E. Mayo Yanes, S. Chakraborty, A. M. Bronstein, R. Gershoni-Poranne, Guided diffusion for inverse molecular design, Nature Computational Science 3(10), 873–882, 2023 detailsE. Schwartz, A. M. Bronstein, R. Giryes, ISP distillation, IEEE Open Journal of Signal Processing 4, 12-20, 2023 detailsT. Blau, R. Ganz, C. Baskin, M. Elad, A. M. Bronstein, Classifier robustness enhancement via test-time transformation, arXiv preprint arXiv:2303.15409 2023 detailsE. Rozenberg, A. Karnieli, O. Yesharim, J. Foley-Comer, S. Trajtenberg-Mills, S. Mishra, S. Prabhakar, R. P. Singh, D. Freedman, A. M. Bronstein, A. Arie, Designing nonlinear photonic crystals for high-dimensional quantum state engineering, ICLR Workshop on Machine Learning for Materials, 2023 detailsE. Rozenberg, A. Karnieli, O. Yesharim, J. Foley-Comer, S. Trajtenberg-Mills, S. Mishra, S. Prabhakar, R. P. Singh, D. Freedman, A. M. Bronstein, A. Arie, A machine learning approach to generate quantum light, ICLR Workshop on Physics for Machine Learning, 2023 detailsH. Ye, S. Vedula, Y. Chen, Y. Yang, A. M. Bronstein, R. Dreslinski, T. Mudge, N. Talati, GRACE: A Scalable Graph-Based Approach to Accelerating Recommendation Model Inference, Proc. ACM Int'l Conf. on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2023 detailsS. Vedula, I. Tallini, A. A. Rosenberg, M. Pegoraro, E. Rodolà, Y. Romano, A. M. Bronstein, Continuous vector quantile regression, Proc. ICML Workshop Frontiers4LCD, 2023 detailsM. Pegoraro, S. Vedula, A. A. Rosenberg, I. Tallini, E. Rodolà, A. M. Bronstein, Vector quantile regression on manifolds, ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023 detailsT. Weiss, A. Wahab, A. M. Bronstein, R. Gershoni-Poranne, Interpretable deep learning unveils structure-property relationships in polybenzenoid hydrocarbons, Journal of Organic Chemistry, 2023 detailsA. A. Rosenberg, S. Vedula, Y. Romano, A. M. Bronstein, Fast nonlinear vector quantile regression, Proc. ICML, 2023 detailsD. Zadok, O. Salzman, A. Wolf, A. M. Bronstein, Towards predicting fine finger motions from ultrasound images via kinematic representation, Proc. ICRA, 2023 detailsA. M. Bronstein, A. Marx, Water stabilizes an alternate turn conformation in horse heart myoglobin, Nature Scientific Reports, 2023 detailsB. Gahtan, R. Cohen, A. M. Bronstein, G. Kedar, Using deep reinforcement learning for mmWave real-time scheduling, Proc. Int'l Conf. Network of the Future (NoF), 2023 detailsT. Shor, T. Weiss, D. Noti, A. M. Bronstein, Multi PILOT: Feasible learned multiple acquisition trajectories for dynamic MRI, Proc. Medical Imaging with Deep Learning (MIDL), 2023 detailsA. B. Bainson, J. Hermanns, P. Petsinis, N. Aavad, C. Dam Larsen, T. Swayne, A. Boyarski, D. Mottin, A. M. Bronstein, P. Karras, Spectral subgraph localization, Proc. Learning on Graphs Conference, 2023 details
- S. A. Maddipatla, N. Bojan Sellam, S. Vedula, A. Marx, A. M. Bronstein, Generative modeling of protein ensembles guided by crystallographic electron densities, NeurIPS Workshop on Machine Learning in Structural Biology (MLSB), 2024 detailsT. Blau, M. Kimhi, Y. Belinkov, A. M. Bronstein, C. Baskin, Context-aware prompt tuning: advancing in-context learning with adversarial methods, arXiv:2410.17222, 2024 detailsB. Gahtan, R. J. Sahala, A. M. Bronstein, R. Cohen, Exploring QUIC dynamics: a large-scale dataset for encrypted traffic analysis, arXiv:2410.03728, 2024 detailsB. Gahtan, S. Funk, E. Kodesh, I. Ketko, T. Kuflik, A. M. Bronstein, Automatic identification and visualization of group training activities using wearable data, arXiv:2410.05452, 2024 detailsB. Gahtan, R. J. Shahla, R. Cohen, A. M. Bronstein, Estimating the number of HTTP/3 responses in QUIC using deep learning, arXiv:2410.06140, 2024 detailsH. Abraham, B. Gahtan, A. Kobovich, O. Leitersdorf, A. M. Bronstein, E. Yaakobi, Beyond the alphabet: deep signal embedding for enhanced DNA clustering, arXiv:2410.06188, 2024 detailsB. Gahtan, R. Cohen, A. M. Bronstein, E. Shapira, Data-driven cellular network selector for vehicle teleoperations, arXiv:2410.19791, 2024 detailsT. Shor, C. Baskin, A. M. Bronstein, Leveraging latents for efficient thermography classification and segmentation, Proc. Medical Imaging with Deep Learning (MIDL), 2024 detailsA. A. Rosenberg, S. Vedula, A. M. Bronstein, A. Marx, Seeing Double: Molecular dynamics simulations reveal the stability of certain alternate protein conformations in crystal structures, bioRxiv 2024.08.31.610605, 2024 detailsS. Vedula, V. Maiorca, L. Basile, F. Locatello, A. M. Bronstein, Scalable unsupervised alignment of general metric and non-metric structures, arXiv preprint arXiv:2406.13507, 2024 (also in Proc. ICML Workshop on AI4Science) detailsA. A. Rosenberg, A. Marx, A. M. Bronstein, A dataset of alternately located segments in protein crystal structures, Scientific Data, 11 (783), 2024 detailsY. Elul, E. Rozenberg, A. Boyarski, Y. Yaniv, A. Schuster, A. M. Bronstein , Data-driven modeling of interrelated dynamical systems, Nature Communications Physics (7), 144, 2024 detailsO. Wengrowicz, A. M. Bronstein, O. Cohen, Unsupervised physics-informed deep learning-based reconstruction for time-resolved imaging by multiplexed ptychography, Optics Express 32(6), pp. 8791-8803, 2024 detailsG. Serussi, T. Shor, T. Hirshberg, C. Baskin, A. M. Bronstein, Active propulsion noise shaping for multi-rotor aircraft localization, Proc. Int'l Conf. on Intelligent Robots and Systems (IROS), 2024 detailsM. Pegoraro, S. Vedula, A. A. Rosenberg, I. Tallini, E. Rodolà, A. M. Bronstein, Vector quantile regression on manifolds, Proc. AIStats, 2024 detailsY. Chen, H. Ye, S. Vedula, A. M. Bronstein, R. Dreslinski, T. Mudge, N. Talati, Demystifying graph sparsification algorithms in graph properties preservation, Proc.Int'l Conf. on Very Large Databases (VLDB), 2024 details
- E. Amrani, L. Karlinsky, A. M. Bronstein, Sample- and parameter-efficient auto-regressive image models, Proc. CVPR, 2025 detailsD. Freedman, E. Rozenberg, A. M. Bronstein, A theoretical framework for an efficient normalizing flow-based solution to the Schrödinger equation, Proc. AAAI, 2025 detailsA. Maddipatla, N. Bojan Sellam, M. Bojan, S. Vedula, P. Schanda, A. Marx, A. M. Bronstein, Inverse problems with experiment-guided AlphaFold, arXiv:2502.09372, 2025 detailsY. Davidson, A. Philipp, S. Chakraborty, A. M. Bronstein, R. Gershoni-Poranne, How local is "local"? Deep learning reveals locality of the induced magnetic field of polycyclic aromatic hydrocarbons, chemrxiv 10.26434/chemrxiv-2025-pqmcc, 2025 details
- E. Amrani, L. Karlinsky, A. M. Bronstein, Sample- and parameter-efficient auto-regressive image models, Proc. CVPR, 2025 detailsD. Freedman, E. Rozenberg, A. M. Bronstein, A theoretical framework for an efficient normalizing flow-based solution to the Schrödinger equation, Proc. AAAI, 2025 detailsA. Maddipatla, N. Bojan Sellam, M. Bojan, S. Vedula, P. Schanda, A. Marx, A. M. Bronstein, Inverse problems with experiment-guided AlphaFold, arXiv:2502.09372, 2025 detailsY. Davidson, A. Philipp, S. Chakraborty, A. M. Bronstein, R. Gershoni-Poranne, How local is "local"? Deep learning reveals locality of the induced magnetic field of polycyclic aromatic hydrocarbons, chemrxiv 10.26434/chemrxiv-2025-pqmcc, 2025 detailsS. A. Maddipatla, N. Bojan Sellam, S. Vedula, A. Marx, A. M. Bronstein, Generative modeling of protein ensembles guided by crystallographic electron densities, NeurIPS Workshop on Machine Learning in Structural Biology (MLSB), 2024 detailsT. Blau, M. Kimhi, Y. Belinkov, A. M. Bronstein, C. Baskin, Context-aware prompt tuning: advancing in-context learning with adversarial methods, arXiv:2410.17222, 2024 detailsB. Gahtan, R. J. Sahala, A. M. Bronstein, R. Cohen, Exploring QUIC dynamics: a large-scale dataset for encrypted traffic analysis, arXiv:2410.03728, 2024 detailsB. Gahtan, S. Funk, E. Kodesh, I. Ketko, T. Kuflik, A. M. Bronstein, Automatic identification and visualization of group training activities using wearable data, arXiv:2410.05452, 2024 detailsB. Gahtan, R. J. Shahla, R. Cohen, A. M. Bronstein, Estimating the number of HTTP/3 responses in QUIC using deep learning, arXiv:2410.06140, 2024 detailsH. Abraham, B. Gahtan, A. Kobovich, O. Leitersdorf, A. M. Bronstein, E. Yaakobi, Beyond the alphabet: deep signal embedding for enhanced DNA clustering, arXiv:2410.06188, 2024 detailsB. Gahtan, R. Cohen, A. M. Bronstein, E. Shapira, Data-driven cellular network selector for vehicle teleoperations, arXiv:2410.19791, 2024 detailsT. Shor, C. Baskin, A. M. Bronstein, Leveraging latents for efficient thermography classification and segmentation, Proc. Medical Imaging with Deep Learning (MIDL), 2024 detailsA. A. Rosenberg, S. Vedula, A. M. Bronstein, A. Marx, Seeing Double: Molecular dynamics simulations reveal the stability of certain alternate protein conformations in crystal structures, bioRxiv 2024.08.31.610605, 2024 detailsS. Vedula, V. Maiorca, L. Basile, F. Locatello, A. M. Bronstein, Scalable unsupervised alignment of general metric and non-metric structures, arXiv preprint arXiv:2406.13507, 2024 (also in Proc. ICML Workshop on AI4Science) detailsA. A. Rosenberg, A. Marx, A. M. Bronstein, A dataset of alternately located segments in protein crystal structures, Scientific Data, 11 (783), 2024 detailsY. Elul, E. Rozenberg, A. Boyarski, Y. Yaniv, A. Schuster, A. M. Bronstein , Data-driven modeling of interrelated dynamical systems, Nature Communications Physics (7), 144, 2024 detailsO. Wengrowicz, A. M. Bronstein, O. Cohen, Unsupervised physics-informed deep learning-based reconstruction for time-resolved imaging by multiplexed ptychography, Optics Express 32(6), pp. 8791-8803, 2024 detailsG. Serussi, T. Shor, T. Hirshberg, C. Baskin, A. M. Bronstein, Active propulsion noise shaping for multi-rotor aircraft localization, Proc. Int'l Conf. on Intelligent Robots and Systems (IROS), 2024 detailsM. Pegoraro, S. Vedula, A. A. Rosenberg, I. Tallini, E. Rodolà, A. M. Bronstein, Vector quantile regression on manifolds, Proc. AIStats, 2024 detailsY. Chen, H. Ye, S. Vedula, A. M. Bronstein, R. Dreslinski, T. Mudge, N. Talati, Demystifying graph sparsification algorithms in graph properties preservation, Proc.Int'l Conf. on Very Large Databases (VLDB), 2024 detailsA. A. Rosenberg, N. Yehishalom, A. Marx, A. M. Bronstein, An amino-domino model described by a cross-peptide-bond Ramachandran plot defines amino acid pairs as local structural units, Proc. US National Academy of Sciences (PNAS), 2023 detailsT. Weiss, L. Cosmo, E. Mayo Yanes, S. Chakraborty, A. M. Bronstein, R. Gershoni-Poranne, Guided diffusion for inverse molecular design, Nature Computational Science 3(10), 873–882, 2023 detailsE. Schwartz, A. M. Bronstein, R. Giryes, ISP distillation, IEEE Open Journal of Signal Processing 4, 12-20, 2023 detailsT. Blau, R. Ganz, C. Baskin, M. Elad, A. M. Bronstein, Classifier robustness enhancement via test-time transformation, arXiv preprint arXiv:2303.15409 2023 detailsE. Rozenberg, A. Karnieli, O. Yesharim, J. Foley-Comer, S. Trajtenberg-Mills, S. Mishra, S. Prabhakar, R. P. Singh, D. Freedman, A. M. Bronstein, A. Arie, Designing nonlinear photonic crystals for high-dimensional quantum state engineering, ICLR Workshop on Machine Learning for Materials, 2023 detailsE. Rozenberg, A. Karnieli, O. Yesharim, J. Foley-Comer, S. Trajtenberg-Mills, S. Mishra, S. Prabhakar, R. P. Singh, D. Freedman, A. M. Bronstein, A. Arie, A machine learning approach to generate quantum light, ICLR Workshop on Physics for Machine Learning, 2023 detailsH. Ye, S. Vedula, Y. Chen, Y. Yang, A. M. Bronstein, R. Dreslinski, T. Mudge, N. Talati, GRACE: A Scalable Graph-Based Approach to Accelerating Recommendation Model Inference, Proc. ACM Int'l Conf. on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2023 detailsS. Vedula, I. Tallini, A. A. Rosenberg, M. Pegoraro, E. Rodolà, Y. Romano, A. M. Bronstein, Continuous vector quantile regression, Proc. ICML Workshop Frontiers4LCD, 2023 detailsM. Pegoraro, S. Vedula, A. A. Rosenberg, I. Tallini, E. Rodolà, A. M. Bronstein, Vector quantile regression on manifolds, ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023 detailsT. Weiss, A. Wahab, A. M. Bronstein, R. Gershoni-Poranne, Interpretable deep learning unveils structure-property relationships in polybenzenoid hydrocarbons, Journal of Organic Chemistry, 2023 detailsA. A. Rosenberg, S. Vedula, Y. Romano, A. M. Bronstein, Fast nonlinear vector quantile regression, Proc. ICML, 2023 detailsD. Zadok, O. Salzman, A. Wolf, A. M. Bronstein, Towards predicting fine finger motions from ultrasound images via kinematic representation, Proc. ICRA, 2023 detailsA. M. Bronstein, A. Marx, Water stabilizes an alternate turn conformation in horse heart myoglobin, Nature Scientific Reports, 2023 detailsB. Gahtan, R. Cohen, A. M. Bronstein, G. Kedar, Using deep reinforcement learning for mmWave real-time scheduling, Proc. Int'l Conf. Network of the Future (NoF), 2023 detailsT. Shor, T. Weiss, D. Noti, A. M. Bronstein, Multi PILOT: Feasible learned multiple acquisition trajectories for dynamic MRI, Proc. Medical Imaging with Deep Learning (MIDL), 2023 detailsA. B. Bainson, J. Hermanns, P. Petsinis, N. Aavad, C. Dam Larsen, T. Swayne, A. Boyarski, D. Mottin, A. M. Bronstein, P. Karras, Spectral subgraph localization, Proc. Learning on Graphs Conference, 2023 detailsJ. Hermanns, A. Tsitsulin, M. Munkhoeva, A. M. Bronstein, D. Mottin, P. Karras, GRASP: Graph Alignment through Spectral Signatures, Proc. Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data, 2022 detailsP. Kang, Z. Lin, Z. Yang, A. M. Bronstein, Q. Li, W. Liu, Deep fused two-step cross-modal hashing with multiple semantic supervision, Multimedia Tools and Applications, 2022 detailsP. Kang, Z. Lin, Z. Yang, X. Fang, A. M. Bronstein, Q. Li, W. Liu, Intra-class low-rank regularization for supervised and semi-supervised cross-modal retrieval, Applied Intelligence, 52(1), pp. 33-54, 2022 detailsY. Nemcovsky, M. Jacoby, A. M. Bronstein, C. Baskin, Physical passive patch adversarial attacks on visual odometry systems, Proc. ACCV, 2022 detailsL. Ackerman-Schraier, A. A. Rosenberg, A. Marx, A. M. Bronstein, Machine learning approaches demonstrate that protein structures carry information about their genetic coding, Nature Scientific Reports, 2022 detailsA. A. Rosenberg, N. Yehishalom, A. Marx, A. M. Bronstein, Defining amino acid pairs as structural units suggests mutation sensitivity to adjacent residues, biorXiv/2022/513383, 2022 detailsA. Rosenberg, A. Marx, A. M. Bronstein, Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon, Nature Communications, 2022 detailsE. Rozenberg, A. Karnieli, O. Yesharim, J. Foley-Comer, S. Trajtenberg-Mills, D. Freedman, A. M. Bronstein, A. Arie, Inverse design of spontaneous parametric downconversion for generation of high-dimensional qudits, Optica 9, 602-615, 2022 detailsN. Talati, H. Ye, S. Vedula, K.-Y. Chen, Y. Chen, D. Liu, Y. Yuan, D. Blaauw, A. M. Bronstein, T. Mudge, R. Dreslinski, Mint: An Accelerator For Mining Temporal Motifs, Proc. MICRO, 2022 detailsE. Zheltonozhskii, C. Baskin, A. Mendelson, A. M. Bronstein, O. Litany, Contrast to divide: Self-supervised pre-training for learning with noisy labels, Proc. of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022 detailsG. Pai, A. Bronstein, R. Talmon, R. Kimmel, Deep isometric maps, Image and Vision Computing, 2022 detailsN. Diamant, N. Shandor, A. M. Bronstein, Delta-GAN-Encoder: Encoding semantic changes for explicit image editing, using few synthetic samples, arXiv:2111.08419, 2022 detailsT. Blau, R. Ganz, B. Kawar, A. M. Bronstein, M. Elad , Threat model-agnostic adversarial defense using diffusion models, arXiv preprint arXiv:2207.08089, 2022 detailsA. Arbelle, S. Doveh, A. Alfassy, J. Shtok, G. Lev, E. Schwartz, H. Kuehne, H. Barak Levi, P. Sattigeri, R. Panda, C.-F. Chen, A. M. Bronstein, K. Saenko, S. Ullman, R. Giryes, R. Feris, L. Karlinsky, Detector-free weakly supervised grounding by separation, Proc. CVPR, 2022 detailsD. E. Fordham, D. Rosentraub, A. L. Polsky, T. Aviram, Y. Wolf, O. Perl, A. Devir, S. Rosentraub, D. H. Silver, Y. Gold Zamir, A. M. Bronstein, M. Lara Lara, J. Ben Nagi, A. Alvarez, S. Munné, Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity?, Human Reproduction, Volume 37, Issue 10, Pages 2275–2290, 2022 detailsS. Doveh, E. Schwartz, C. Xue, R. Feris, A. M. Bronstein, R. Giryes, L. Karlinsky, MetAdapt: Meta-learned task-adaptive architecture for few-shot classification, Pattern Recognition Letters, 2021 detailsT. Weiss, N. Peretz, S. Vedula, A. Feuer, A. M. Bronstein, Joint optimization of system design and reconstruction in MIMO radar imaging, Proc. IEEE Int'l Workshop on Machine Learning for Signal Processing, 2021 detailsY. Nahshan, B. Chmiel, C. Baskin, E. Zheltonozhskii, R. Banner, A. M. Bronstein, A. Mendelson, Loss aware post-training quantization, Machine Learning, 2021 detailsC. Baskin, B. Chmiel, E. Zheltonozhskii, R. Banner, A. M. Bronstein, A. Mendelson, CAT: Compression-aware training for bandwidth reduction, JMLR, 2021 detailsE. Amrani, A. M. Bronstein, Self-supervised classification network, Proc. ECCV, 2022 detailsE. Rozenberg, D. Freedman, A. M. Bronstein, Learning to localize objects using limited annotation with applications to thoracic diseases, IEEE Access Vol. 9, 2021 detailsT. Weiss, O. Senouf, S. Vedula, O. Michailovich, M. Zibulevsky, A. M. Bronstein, PILOT: Physics-Informed Learned Optimal Trajectories for accelerated MRI, Journal of Machine Learning for Biomedical Imaging (MELBA), 2021 detailsY. Elul, A. Rosenberg, A. Schuster, A. M. Bronstein, Y. Yaniv, Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis, Proc. US National Academy of Sciences (PNAS), 2021 detailsL. Karlinsky, J. Shtok, A. Alfassy, M. Lichtenstein, S. Harary, E. Schwartz, S. Doveh, P. Sattigeri, R. Feris, A. M. Bronstein, R. Giryes, StarNet: towards weakly supervised few-shot detection and explainable few-shot classification, Proc. AAAI, 2021 detailsE. Amrani, R. Ben-Ari, D. Rotman, A. M. Bronstein, Noise estimation using density estimation for self-supervised multimodal learning, Proc. AAAI, 2021 detailsO. Dahary, M. Jacoby, A. M. Bronstein, Digital Gimbal: End-to-end deep image stabilization with learnable exposure times, Proc. CVPR, 2021 detailsA. Boyarski, S. Vedula, A. M. Bronstein, Spectral geometric matrix completion, Proc. Mathematical and Scientific Machine Learning, 2021 detailsE. Rozenberg, A. Karnieli, O. Yesharim, S. Trajtenberg-Mills, D. Freedman, A. M. Bronstein, A. Arie, Inverse design of quantum holograms in three-dimensional nonlinear photonic crystals, CLEO, 2021 detailsA. Karbachevsky, C. Baskin, E. Zheltonozshkii, Y. Yermolin, F. Gabbay, A. M. Bronstein, A. Mendelson, Early-stage neural network hardware performance analysis, Sustainability 13(2):717, 2021 detailsC. Baskin, E. Schwartz, E. Zheltonozhskii, N. Liss, R. Giryes, A. M. Bronstein, A. Mendelson, UNIQ: Uniform noise injection for non-uniform quantization of neural networks, ACM Transactions on Computer Systems (TOCS), 2020 detailsB. Finkelshtein, C. Baskin, E. Zheltonozhskii, U. Alon, Single-node attack for fooling graph neural networks, arXiv:2011.03574, 2020 detailsJ. Alush-Aben, L. Ackerman-Schraier, T. Weiss, S. Vedula, O. Senouf, A. M. Bronstein, 3D FLAT: Feasible Learned Acquisition Trajectories for Accelerated MRI, Proc. Machine Learning for Medical Image Reconstruction, MICCAI 2020 detailsT. Weiss, S. Vedula, O. Senouf, O. Michailovich, A. M. Bronstein, Towards learned optimal q-space sampling in diffusion MRI, Proc. Computational Diffusion MRI, MICCAI 2020 detailsE. Zheltonozhskii, C. Baskin, A. M. Bronstein, A. Mendelson, Self-supervised learning for large-scale unsupervised image clustering, NeurIPS 2020 Workshop: Self-Supervised Learning - Theory and Practice, 2020 detailsG. Mariani, L. Cosmo, A. M. Bronstein, E. Rodolà, Generating adversarial surfaces via band-limited perturbations, Computer Graphics Forum, 2020 detailsB. Chmiel, C. Baskin, R. Banner, E. Zheltonozshkii, Y. Yermolin, A. Karbachevsky, A. M. Bronstein, A. Mendelson, Feature map transform coding for energy-efficient CNN inference, Proc. Intl. Joint Conf. on Neural Networks (IJCNN), 2020 detailsE. Amrani, R. Ben-Ari, T. Hakim, A. M. Bronstein, Self-Supervised Object Detection and Retrieval Using Unlabeled Videos, CVPR workshop, 2020 detailsD. H. Silver, M. Feder, Y. Gold-Zamir, A. L. Polsky, S. Rosentraub, E. Shachor, A. Weinberger, P. Mazur, V. D. Zukin, A. M. Bronstein, Data-driven prediction of embryo implantation probability using IVF time-lapse imaging, Proc. MIDL, 2020 detailsT. Weiss, S. Vedula, O. Senouf, A. M. Bronstein, O. Michailovich, M. Zibulevsky, Joint learning of Cartesian undersampling and reconstruction for accelerated MRI, Proc. Int’l Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2020 detailsS. Sommer, A. M. Bronstein, Horizontal flows and manifold stochastics in geometric deep learning, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), 2020 detailsK. Rotker, D. Ben-Bashat, A. M. Bronstein, Over-parameterized models for vector fields, SIAM Journal on Imaging Sciences (SIIMS), 2020 detailsA. Tsitsulin, M. Munkhoeva, D. Mottin, P. Karras. A. M. Bronstein, I. Oseledets, E. Müller, Intrinsic multi-scale evaluation of generative models, Proc. ICLR, 2020 detailsA. Karbachevsky, C. Baskin, E. Zheltonozshkii, Y. Yermolin, F. Gabbay, A. M. Bronstein, A. Mendelson, HCM: Hardware-aware complexity metric for neural network architectures, arXiv:2004.08906, 2020 detailsE. Zheltonozhskii, C. Baskin, Y. Nemcovsky, B. Chmiel, A. Mendelson, A. M. Bronstein, Colored noise injection for training adversarially robust neural networks, arXiv:2003.02188, 2020 detailsA. Livne, A. M. Bronstein, R. Kimmel, Z. Aviv, S. Grofit, Do we need depth in state-of-the-art face authentication?, Proc. IEEE Int'l Conf. on 3D Vision (3DV), 2020 detailsM. Shkolnik, B. Chmiel, R. Banner, G. Shomron, Y. Nahshan, A. M. Bronstein, U. Weiser, Robust Quantization: One Model to Rule Them All, Proc. NeurIPS, 2020 detailsY. Choukroun , A. Shtern, A. M. Bronstein, R. Kimmel, Hamiltonian operator for spectral shape analysis, IEEE Trans. Vis. and Comp. Graphics, vol. 26(2), 2020 detailsA. Boyarski, S. Vedula, A. M. Bronstein, Deep matrix factorization with spectral geometric regularization, arXiv: 1911.07255, 2019 detailsY. Nahshan, B. Chmiel, C. Baskin, E. Zheltonozhskii, R. Banner, A. M. Bronstein, A. Mendelson, Loss aware post-training quantization, arXiv: 1911.07190, 2019 detailsY. Nemcovsky, E. Zheltonozhskii, C. Baskin, B. Chmiel, A. M. Bronstein, A. Mendelson, Smoothed inference for adversarially-trained models, arXiv: 1911.07198, 2019 detailsS. Doveh, E. Schwartz, C. Xue, R. Feris, A. M. Bronstein, R. Giryes, L. Karlinsky, MetAdapt: Meta-learned task-adaptive architecture for few-shot classification, arXiv: 1912.00412, 2019 detailsE. Rozenberg, D. Freedman, A. M. Bronstein, Localization with limited annotation for chest X-rays, Proc. ML4H, NeurIPS, 2019 detailsS. Vedula, O. Senouf, G. Zurakov, A. M. Bronstein, O. Michailovich, M. Zibulevsky, Learning beamforming in ultrasound imaging, Proc. Medical Imaging with Deep Learning (MIDL), 2019 detailsE. Schwartz, L. Karlinsky, J. Shtok, S. Harary, M. Marder, R. Feris, A. Kumar, R. Giryes, A. M. Bronstein, RepMet: Representative-based metric learning for classification and one-shot object detection, Proc. Computer Vision and Pattern Recognition (CVPR), 2019 detailsO. Halimi, O. Litany, E. Rodolà, A. M. Bronstein, R. Kimmel, Self-supervised learning of dense shape correspondence, Proc. Computer Vision and Pattern Recognition (CVPR), 2019 detailsA. Alfassy, L. Karlinsky, A. Aides, J. Shtok, S. Harary, R. Feris, R. Giryes, A. M. Bronstein, LaSO: Label-Set Operations networks for multi-label few-shot learning, Proc. Computer Vision and Pattern Recognition (CVPR), 2019 detailsA. Zabatani, V. Surazhsky, E. Sperling, S. Ben Moshe, O. Menashe, D. H. Silver, Z. Karni, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Intel RealSense SR300 Coded light depth Camera, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), 2019 detailsY. Zur, C. Baskin, E. Zheltonozhskii, B. Chmiel, I. Evron, A. M. Bronstein, A. Mendelson, Towards learning of filter-level heterogeneous compression of convolutional neural networks, Proc. AutoML Workshop, Int'l Conf. on Machine Learning (ICML), 2019 detailsE. Schwartz, L. Karlinsky, R. Feris, R. Giryes, A. M. Bronstein, Baby steps towards few-shot learning with multiple semantics, arXiv:1906.01905, 2019 detailsA. Rampini, I. Tallini, M. Ovsjanikov, A. M. Bronstein, E. Rodola, Correspondence-free region localization for partial shape similarity via Hamiltonian spectrum alignment, Proc. 3D Vision (3DV), 2019 (Best paper award) detailsO. Senouf, S. Vedula, T. Weiss, A. M. Bronstein, O. Michailovich, M. Zibulevsky, Self-supervised learning of inverse problem solvers in medical imaging, Proc. Medical Image Learning with Less Labels and Imperfect Data, MICCAI 2019 detailsR. M. Dyke, C Stride, Y.-K. Lai, P. L. Rosin, M. Aubry, A. Boyarski, A. M. Bronstein, M. M. Bronstein, D. Cremers, M. Fisher, T. Groueix, D. Guo, V. G. Kim, R. Kimmel, Z. Lähner, K. Li, O. Litany, T. Remez, E. Rodolà, B. C. Russell, Y. Sahillioglu, R. Slossberg, M. Vestner, Z. Wu, J. Yang, Gary Tam, Shape Correspondence with Isometric and Non-Isometric Deformations, Eurographics Workshop on 3D Object Retrieval, 2019 detailsN. Diamant, D. Zadok, C. Baskin, E. Schwartz, A. M. Bronstein, Beholder-GAN: Generation and beautification of facial images with conditioning on their beauty level, Proc. Int'l Conf. on Image Processing (ICIP), 2019 detailsG. Pai, R. Talmon, A. M. Bronstein, R. Kimmel, DIMAL: Deep isometric manifold learning using sparse geodesic sampling, Proc. IEEE Winter Conf. on Applications of Computer Vision (WACV), 2019 detailsO. Litany, E. Rodolà, A. M. Bronstein, M. M. Bronstein, D. Cremers, Partial single- and multi-shape dense correspondence using functional maps, Chapter in The Handbook of Numerical Analysis - Processing, Analyzing and Learning of Images, Shapes, and Forms, Elsevier, 2019 detailsA. Boyarski, A. M. Bronstein, Multidimensional scaling, Computer Vision: A Reference Guide, (Katsushi Ikeuchi, Ed.) detailsE. Schwartz, L. Karlinsky, J. Shtok, S. Harary, M. Marder, R. Feris, A. Kumar, R. Giryes, A. M. Bronstein, ∆-encoder: an effective sample synthesis method for few-shot object recognition, Proc. Neural Information Processing Systems (NIPS), 2018 detailsE. Rodolà, Z. Lähner, A. M. Bronstein, M. M. Bronstein, J. Solomon, Functional maps representation on product manifolds, arXiv:1809.10940, 2018 detailsC. Baskin, N. Liss, Y. Chai, E. Zheltonozhskii, E. Schwartz, R. Giryes, A. Mendelson, A. M. Bronstein, NICE: noise injection and clamping estimation for neural network quantization, arXiv:1810.00162, 2018 detailsQ. Qiu, J. Lezama, A. M. Bronstein, G. Sapiro, ForestHash: Semantic hashing with shallow random forests and tiny convolutional networks, Proc. European Conf. on Computer Vision (ECCV), 2018 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Class-aware fully-convolutional Gaussian and Poisson denoising, IEEE Trans. Image Processing, Vol. 27(11), 2018 detailsA. Tsitsulin, D. Mottin, P. Karras, A. M. Bronstein, E, Mueller, NetLSD: Hearing the shape of a graph, Proc. ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), 2018 detailsO. Senouf, S. Vedula, G. Zurakhov, A. M. Bronstein, M. Zibulevsky, O. Michailovich, D. Adam, D. Blondheim, High frame-rate cardiac ultrasound imaging with deep learning, Proc. Int'l Conf. Medical Image Computing & Computer Assisted Intervention (MICCAI), 2018 detailsS. Vedula, O. Senouf, G. Zurakhov, A. M. Bronstein, M. Zibulevsky, O. Michailovich, D. Adam, D. Gaitini, High quality ultrasonic multi-line transmission through deep learning, Proc. Machine Learning for Medical Image Reconstruction (MLMIR), 2018 detailsA. Tsitsulin, D. Mottin, P. Karras, A. M. Bronstein, E, Mueller, SGR: Self-supervised spectral graph representation learning, Proc. KDD Deep Learning Day, 2018 detailsE. Schwartz, R. Giryes, A. M. Bronstein, DeepISP: Towards learning an end-to-end image processing pipeline, IEEE Trans. on Image Processing, 2018 detailsH. Haim, S. Elmalem, R. Giryes, A. M. Bronstein, E. Marom, Depth estimation from a single image using deep learned phase coded mask, IEEE Trans. Computational Imaging, Vol. 2(3), 2018 (Winner of the OSA Student Grand Challenge The Optical System of the Future) detailsE. Tsitsin, A. M. Bronstein, T. Hendler, M. Medvedovsky, Passive electric impedance tomography, Proc. Electric Impedance Tomography (EIT), 2018 detailsE. Tsitsin, T. Mund, A. M. Bronstein, Printable anisotropic phantom for EEG with distributed current sources, Proc. IEEE Int'l Symposium on Biomedical Imaging (ISBI), 2018 detailsE. Tsitsin, M. Medvedovsky, A. M. Bronstein, VibroEEG: Improved EEG source reconstruction by combined acoustic-electric imaging, Proc. IEEE Int'l Symposium on Biomedical Imaging (ISBI), 2018 detailsC. Baskin, N. Liss, E. Zheltonozhskii, A. M. Bronstein, A. Mendelson, Streaming architectures for large-scale quantized neural networks on an FPGA-based dataflow platform, IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2018 detailsR. Giryes, Y. C. Eldar, A. M. Bronstein, G. Sapiro, Tradeoffs between convergence speed and reconstruction accuracy in inverse problems, IEEE Trans. on Signal Processing, Vol. 66(7), 2018 detailsS. Vedula, O. Senouf, A. M. Bronstein, O. V. Michailovich, M. Zibulevsky, Towards CT-quality ultrasound imaging using deep learning, arXiv:1710.06304, 2017 detailsO. Litany, T. Remez, E. Rodolà, A. M. Bronstein, M. M. Bronstein, Deep Functional Maps: Structured prediction for dense shape correspondence, Proc. Int'l Conf. on Computer Vision (ICCV), 2017 detailsZ. Laehner, M. Vestner, A. Boyarski, O. Litany, R. Slossberg, T. Remez, E. Rodolà, A. M. Bronstein, M. M. Bronstein, R. Kimmel, D. Cremers, Efficient deformable shape correspondence via kernel matching, Proc. 3D Vision (3DV), 2017 detailsG. Alexandroni, Y. Podolsky, H. Greenspan, T. Remez, O. Litany, A. M. Bronstein, R. Giryes, White matter fiber representation using continuous dictionary learning, Proc. Int'l Conf. Medical Image Computing & Computer Assisted Intervention (MICCAI), 2017 detailsM. Vestner, R. Litman, E. Rodolà, A. M. Bronstein, D. Cremers, Product Manifold Filter: Non-rigid shape correspondence via kernel density estimation in the product space, Proc. Computer Vision and Pattern Recognition (CVPR), 2017 detailsO. Litany, E. Rodolà, A. M. Bronstein, M. M. Bronstein, Fully spectral partial shape matching, Computer Graphics Forum, Vol. 36(2), 2017 detailsA. Boyarski, A. M. Bronstein, M. M. Bronstein, Subspace least squares multidimensional scaling, Proc. Scale Space and Variational Methods (SSVM), 2017 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Deep class-aware image denoising, Proc. Int'l Conf. on Image Processing (ICIP), 2017 detailsO. Litany, T. Remez, A. M. Bronstein, Cloud Dictionary: Sparse coding and modeling for point clouds, arXiv:1612.04956, 2017 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Deep class-aware denoising, arXiv:1701.01698, 2017 detailsT. Remez, O. Litany, R. Giryes, A. M. Bronstein, Deep convolutional denoising of low-light images, arXiv:1701.01687, 2017 detailsO. Litany, T. Remez, D. Freedman, L. Shapira, A. M. Bronstein, R. Gal, ASIST: Automatic Semantically Invariant Scene Transformation, Computer Vision and Image Understanding, Vol. 157, 2017 detailsM. Ovsjanikov, E. Corman, M. M. Bronstein, E. Rodolà, M. Ben-Chen, L. Guibas, F. Chazal, A. M. Bronstein, Computing and processing correspondences with functional maps, SIGGRAPH Courses, 2017 detailsY. Choukroun, A. Shtern, A. M. Bronstein, R. Kimmel, Hamiltonian operator for spectral shape analysis, arXiv:1611.01990, 2016 detailsA. M. Bronstein, Y. Choukroun, R. Kimmel, M. Sela, Consistent discretization and minimization of the L1 norm on manifolds, Proc. 3D Vision (3DV), 2016 detailsR. Litman, A. M. Bronstein, SpectroMeter: Amortized sublinear spectral approximation of distance on graphs, Proc. 3D Vision (3DV), 2016 detailsT. Remez, O. Litany, S. Yoseff, H. Haim, A. M. Bronstein, FPGA system for real-time computational extended depth of field imaging using phase aperture coding, arXiv:1608.01074, 2016 detailsR. Giryes, G. Sapiro, A. M. Bronstein, Deep neural networks with random Gaussian weights: A universal classification strategy?, IEEE Trans. Signal Processing, Vol. 64(13), 2016 detailsO. Litany, E. Rodolà, A. M. Bronstein, M. M. Bronstein, D. Cremers, Non-rigid puzzles, Computer Graphics Forum, Vol. 35(5), 2016 (SGP Best Paper Award) detailsX. Bian, H. Krim, A. M. Bronstein, L. Dai, Sparsity and nullity: paradigms for analysis dictionary learning, SIAM J. Imaging Sci., Vol. 9(3), 2016 detailsD. Pickup, X. Sun, P. L. Rosin, R. R. Martin, Z. Cheng, Z. Lian, M. Aono, A. Ben Hamza, A. M. Bronstein, M. M. Bronstein, S. Bu, U. Castellani, S. Cheng, V. Garro, A. Giachetti, A. Godil, J. Han, H. Johan, L. Lai, B. Li, C. Li, H. Li, R. Litman, X. Liu, Z. Liu, Y. Lu, A. Tatsuma, J. Ye, Shape retrieval of non-rigid 3D human models, Intl. Journal of Computer Vision (IJCV), 2016 detailsO. Litany, T. Remez, A. M. Bronstein, Image reconstruction from dense binary pixels, arXiv:1512.01774, 2015D. Eynard, A. Kovnatsky, M. M. Bronstein, K. Glashoff, A. M. Bronstein, Multimodal manifold analysis using simultaneous diagonalization of Laplacians, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 37(12), 2015 detailsT. Remez, O. Litany, A. M. Bronstein, A Picture is Worth a Billion Bits: Real-time image reconstruction from dense binary pixels, arXiv:1510.04601, 2015 detailsA. M. Bronstein, New dimensions of media, Universidad La Salle, Revista de ciencias de la computación, Vol. 3(1), 2015H. Haim, A. M. Bronstein, E. Marom, Computational all-in-focus imaging using an optical phase mask, OSA Optics Express, Vol. 23(19), 2015 detailsR. Litman, S. Korman, A. M. Bronstein, S. Avidan, GMD: Global model detection via inlier rate estimation, Proc. Computer Vision and Pattern Recognition (CVPR), 2015 detailsI. Sipiran, B. Bustos, T. Schreck, A. M. Bronstein, M. M. Bronstein, U. Castellani, S. Choi, L. Lai, H. Li, R. Litman, L. Sun, SHREC'15 Track: Scalability of non-rigid 3D shape retrieval, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2015 detailsX. Bian, H. Krim, A. M. Bronstein, L. Dai, Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis, Proc. Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2015 detailsY. Aflalo, A. M. Bronstein, R. Kimmel, On convex relaxation of graph isomorphism, Proc. US National Academy of Sciences (PNAS), 2015 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Learning efficient sparse and low-rank models, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 37(9), 2015 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Supervised non-negative matrix factorization for audio source separation, Chapter in Excursions in Harmonic Analysis (R. Balan, M. Begue, J. J. Benedetto, W. Czaja, K. Okoudjou Eds.), Birkhaeuser, 2015 detailsQ. Qiu, G. Sapiro, A. M. Bronstein, Random forests can hash, arXiv:1412.5083, 2014 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Supervised non-Euclidean sparse NMF via bilevel optimization with applications to speech enhancement, Proc. Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA), 2014 detailsS. Korman, R. Litman, S. Avidan, A. M. Bronstein, Probably approximately symmetric: Fast rigid symmetry detection with global guarantees, Computer Graphics Forum (CGF), Vol. 34(1), 2014 detailsR. Litman, A. M. Bronstein, M. M. Bronstein, U. Castellani, Supervised learning of bag-of-features shape descriptors using sparse coding, Computer Graphics Forum (CGF), Vol. 33(5), 2014 detailsO. Menashe, A. M. Bronstein, Real-time compressed imaging of scattering volumes, Proc. Int'l Conf. on Image Processing (ICIP), 2014 detailsS. Biasotti, A. Cerri, A. M. Bronstein, M. M. Bronstein, Quantifying 3D shape similarity using maps: Recent trends, applications and perspectives, Proc. EUROGRAPHICS STARS, 2014 detailsJ. Masci, M. M. Bronstein, A. M. Bronstein, J. Schmidhuber, Multimodal similarity-preserving hashing, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 36(4), 2014 detailsJ. Masci, A. M. Bronstein, M. M. Bronstein, P. Sprechmann, G. Sapiro, Sparse similarity-preserving hashing, Proc. Int'l Conf. on Learning Representations (ICLR), 2014 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Equi-affine invariant intrinsic geometries for bendable shapes analysis, Journal of Mathematical Imaging and Vision (JMIV), Vol. 50(1), 2014 detailsD. Pickup, X. Sun, P. L. Rosin, R. R. Martin, Z. Cheng, Z. Lian, M. Aono, A. Ben Hamza, A. M. Bronstein, M. M. Bronstein, S. Bu, U. Castellani, S. Cheng, V. Garro, A. Giachetti, A. Godil, J. Han, H. Johan, L. Lai, B. Li, C. Li, H. Li, R. Litman, X. Liu, Z. Liu, Y. Lu, A. Tatsuma, J. Ye, Shape retrieval of non-rigid 3D human models, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2014 detailsP. Sprechmann, R. Litman, T. Ben Yakar, A. M. Bronstein, G. Sapiro, Efficient supervised sparse analysis and synthesis operators, Proc. Neural Information Proc. Systems (NIPS), 2013 detailsT. Ben Yakar, R. Litman, P. Sprechmann, A. M. Bronstein, G. Sapiro, Bilevel sparse models for polyphonic music transcription, Proc. Annual Conf. of the Int'l Society for Music Info. Retrieval (ISMIR), 2013 detailsJ. Pokrass, A. M. Bronstein, M. M. Bronstein, P. Sprechmann, G. Sapiro, Sparse modeling of intrinsic correspondences, Computer Graphics Forum (CGF), Vol. 32(2), 2013 detailsA. Kovnatsky, M. M. Bronstein, A. M. Bronstein, K. Glashoff, R. Kimmel, Coupled quasi-harmonic bases, Computer Graphics Forum (CGF), Vol. 32(2), 2013 detailsP. Sprechmann, A. M. Bronstein, J.-M. Morel, G. Sapiro, Audio restoration from multiple copies, Proc. Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2013 detailsP. Sprechmann, A. M. Bronstein, M. M. Bronstein, G. Sapiro, Learnable low rank sparse models for speech denoising, Proc. Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2013 detailsA. Kovnatski, D. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Geometric and photometric data fusion in non-rigid shape analysis, Numerical Mathematics: Theory, Methods and Applications (NM-TMA), Vol. 6(1), 2013 detailsJ. Pokrass, A. M. Bronstein, M. M. Bronstein, Partial shape matching without point-wise correspondence, Numerical Mathematics: Theory, Methods and Applications (NM-TMA), Vol. 6(1), 2013 detailsR. Litman, and A. M. Bronstein, Learning spectral descriptors for deformable shape correspondence, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 36(1), 2013 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Real-time online singing voice separation from monaural recordings using robust low-rank modeling, Proc. Annual Conference of the Int'l Society for Music Information Retrieval (ISMIR), 2012 (Best poster presentation award) detailsO. Litany, A. M. Bronstein, M. M. Bronstein, Putting the pieces together: regularized multi-shape partial matching, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012 detailsA. Kovnatsky, A. M. Bronstein, M. M. Bronstein, Stable spectral mesh filtering, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012 detailsI. Kokkinos, M. M. Bronstein, R. Litman, A. M. Bronstein, Intrinsic shape context descriptors for deformable shapes, Proc. Computer Vision and Pattern Recognition (CVPR), 2012 detailsE. Rodolà, A. M. Bronstein, A. Albarelli, F. Bergamasco, A. Torsello, A game-theoretic approach to deformable shape matching, Proc. Computer Vision and Pattern Recognition (CVPR), 2012 detailsM. Spagnuolo, M. M. Bronstein, A. M. Bronstein, A. Ferreira (Eds.), Eurographics Workshop on 3D Object Retrieval, Eurographics Association, 2012, ISBN: 978-3-905674-36-1 detailsR. Litman, A. M. Bronstein, M. M. Bronstein, Stable volumetric features in deformable shapes, Computers and Graphics (CAG), Vol. 36(5), 2012 detailsG. Rosman, A. M. Bronstein, M. M. Bronstein, X.-C. Tai, R. Kimmel, Group-valued regularization for analysis of articulated motion, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012 detailsP. Sprechmann, A. M. Bronstein, G. Sapiro, Learning efficient structured sparse models, Proc. Int'l Conf. on Machine Learning (ICML), 2012 detailsA. Zabatani, A. M. Bronstein, Parallelized algorithms for rigid surface alignment on GPU, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2012 detailsG. Rosman, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Articulated motion segmentation of point clouds by group-valued regularization, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2012 detailsA. Kovnatsky, M. M. Bronstein, A. M. Bronstein, D. Raviv, R. Kimmel, Affine-invariant photometric heat kernel signatures, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2012 detailsC. Strecha, A. M. Bronstein, M. M. Bronstein, P. Fua, LDAHash: improved matching with smaller descriptors, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 34(1), 2012 detailsB. M. Bruckstein, B. ter haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.), Scale Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science (LNCS) No. 6667, Springer, 2012, ISBN: 978-3-642-24784-2 detailsR. Litman, A. M. Bronstein, M. M. Bronstein, Stable semi-local features for non-rigid shapes, Chapter in Innovations for Shape Analysis: Models and Algorithms (M. Breuss, A. M. Bruckstein, P. Maragos Eds.), Springer, 2012 detailsG. Rosman, M. M. Bronstein, A. M. Bronstein, A. Wolf, R. Kimmel, Group-valued regularization for motion segmentation of articulated shapes, Chapter in Innovations for Shape Analysis: Models and Algorithms (M. Breuss, A. M. Bruckstein, P. Maragos Eds.), Springer, 2012 detailsA. M. Bronstein, M. M. Bronstein, M. Ovsjanikov, 3D features, surface descriptors, and object descriptors, Chapter in 3D Imaging, Analysis and Applications (N. Pears, Y. Liu, P. Bunting, Eds.), Springer, 2012. detailsR. Kimmel, C. Zhang, A. M. Bronstein, M. M. Bronstein, Are MSER features really interesting?, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 33(11), 2011 detailsA. M. Bronstein, Spectral descriptors for deformable shapes, arXiv:1110.5015, 2011 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant diffusion geometry for the analysis of deformable 3D shapes, Proc. Computer Vision and Pattern Recognition (CVPR), 2011 detailsM. M. Bronstein, A. M. Bronstein, Shape recognition with spectral distances, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 33(5), 2011 detailsJ. Pokrass, A. M. Bronstein, M. M. Bronstein, A correspondence-less approach to matching of deformable shapes, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsA. Kovnatsky, M. M. Bronstein, A. M. Bronstein, R. Kimmel, Photometric heat kernel signatures, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsJ. Aflalo, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Deformable shape retrieval by learning diffusion kernels, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsG. Rosman, M. M. Bronstein, A. M. Bronstein, A. Wolf, R. Kimmel, Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsC. Wang, M. M. Bronstein, A. M. Bronstein, N. Paragios, Discrete minimum distortion correspondence problems for non-rigid shape matching, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsA. Hooda, M. M. Bronstein, A. M. Bronstein, R. Horaud, Shape palindromes: analysis of intrinsic symmetries in 2D articulated shapes, Proc. Scale Space and Variational Methods (SSVM), 2011 detailsF. Michel, M. M. Bronstein, A. M. Bronstein, N. Paragios, Boosted metric learning for 3D multi-modal deformable registration, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2011 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant geodesic geometry of deformable 3D shapes, Computers and Graphics (CAG), Vol. 35(3), 2011 detailsR. Litman, A. M. Bronstein, A. M. Bronstein, Diffusion-geometric maximally stable component detection in deformable shapes, Computers and Graphics (CAG), Vol. 35(3), 2011 detailsA. M. Bronstein, M. M. Bronstein, M. Ovsjanikov, L. J. Guibas, Shape Google: geometric words and expressions for invariant shape retrieval, ACM Trans. Graphics (TOG), Vol. 30(1), 2011 detailsA. M. Bronstein, M. M. Bronstein, Metric approaches to invariant shape similarity, Chapter in Handbook of Mathematical Methods in Imaging (O. Scherzer Ed.), Springer, 2011 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant geodesic geometry of deformable 3D shapes, arXiv:1012.5936, 2010 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, N. Sochen, Affine-invariant diffusion geometry for the analysis of deformable 3D shapes, arXiv:1012.5933, 2010 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Full and partial symmetries of non-rigid shapes, Int'l Journal of Computer Vision (IJCV), Vol. 89(1), 2010 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, M. Mahmoudi, G. Sapiro, A Gromov-Hausdorff framework with diffusion geometry for topologically-robust non-rigid shape matching, Int'l Journal of Computer Vision (IJCV), Vol. 89(2), 2010 detailsN. Mitra, A. M. Bronstein, M. M. Bronstein, Intrinsic regularity detection in 3D geometry, Proc. European Conf. Computer Vision (ECCV), 2010 detailsA. M. Bronstein, M. M. Bronstein, Spatially-sensitive affine-invariant image descriptors, Proc. European Conf. Computer Vision (ECCV), 2010 detailsM. M. Bronstein, A. M. Bronstein, F. Michel, N. Paragios, Data fusion through cross-modality metric learning using similarity-sensitive hashing, Proc. Computer Vision and Pattern Recognition (CVPR), 2010 detailsD. Raviv, M. M. Bronstein, A. M. Bronstein, R. Kimmel, Volumetric heat kernel signatures, Proc. Int'l Workshop on 3D Object Retrieval (3DOR), ACM Multimedia, 2010 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, G. Sapiro, Diffusion symmetries of non-rigid shapes, Proc. Int'l Symposium on 3D Data Processing, Visualization and Transmission (3DPVT), 2010 detailsG. Rosman, M. M. Bronstein, A. M. Bronstein, R. Kimmel, Nonlinear dimensionality reduction by topologically constrained isometric embedding, Intl. Journal of Computer Vision (IJCV), Vol. 89(1), 2010 detailsA. M. Bronstein, M. M. Bronstein, U. Castellani, B. Falcidieno, A. Fusiello, A. Godil, L. J. Guibas, I. Kokkinos, Z. Lian, M. Ovsjanikov, G. Patané, M. Spagnuolo, R. Toldo, SHREC 2010: robust large-scale shape retrieval benchmark, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2010 detailsA. M. Bronstein, M. M. Bronstein, B. Bustos, U. Castellani, M. Crisani, B. Falcidieno, L. J. Guibas, I. Kokkinos, V. Murino, M. Ovsjanikov, G. Patané, I. Sipiran, M. Spagnuolo, J. Sun, SHREC 2010: robust feature detection and description benchmark, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2010 detailsA. M. Bronstein, M. M. Bronstein, U. Castellani, A. Dubrovina, L. J. Guibas, R. P. Horaud, R. Kimmel, D. Knossow, E. von Lavante, D. Mateus, M. Ovsjanikov, A. Sharma, SHREC 2010: robust correspondence benchmark, Proc. EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2010 detailsO. Rubinstein, Y. Honen, A. M. Bronstein, M. M. Bronstein, R. Kimmel, 3D color video camera, Proc. Workshop on 3D Digital Imaging and Modeling (3DIM), 2009 detailsM. Ovsjanikov, A. M. Bronstein, M. M. Bronstein, L. Guibas, ShapeGoogle: a computer vision approach for invariant shape retrieval, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2009 detailsY. Devir, G. Rosman, A. M. Bronstein, M. M. Bronstein, R. Kimmel, On reconstruction of non-rigid shapes with intrinsic regularization, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2009 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Topology-invariant similarity of nonrigid shapes, Int'l Journal of Computer Vision (IJCV), Vol. 81(3), 2009 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Partial similarity of objects, or how to compare a centaur to a horse, Int'l Journal of Computer Vision (IJCV), Vol. 84(2), 2009 detailsA. M. Bronstein, M. M. Bronstein, Y. Carmon, R. Kimmel, Partial similarity of shapes using a statistical significance measure, IPSJ Trans. Computer Vision and Application, Vol. 1, 2009 detailsO. Weber, Y. Devir, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Parallel algorithms for approximation of distance maps on parametric surfaces, ACM Trans. on Graphics, Vol. 27(4), 2008 detailsA. M. Bronstein, M. M. Bronstein, Regularized partial matching of rigid shapes, Proc. European Conf. on Computer Vision (ECCV), 2008 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Analysis of two-dimensional non-rigid shapes, Int'l Journal of Computer Vision (IJCV), Vol. 78(1), 2008 detailsA. M. Bronstein, M. M. Bronstein, Not only size matters: regularized partial matching of nonrigid shapes, Proc. Workshop on Nonrigid Shape Analysis and Deformable Image Registration (NORDIA), 2008 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Numerical geometry of non-rigid shapes, Springer, 2008, ISBN: 978-0387733005 detailsG. Rosman, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Topologically constrained isometric embedding, Human Motion Understanding, Modeling, Capture, and Animation, Computational Imaging and Vision, Vol. 36, Springer, 2008 detailsR. Giryes, A. M. Bronstein, Y. Moshe, M. M. Bronstein, Embedded system for 3D shape reconstruction, Proc. European DSP Education and Research Symposium (EDERS), 2008 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Calculus of non-rigid surfaces for geometry and texture manipulation, IEEE Trans. Visualization and Computer Graphics, Vol 13(5), 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Rock, Paper, and Scissors: extrinsic vs. intrinsic similarity of non-rigid shapes, Proc. Int'l Conf. Computer Vision (ICCV), 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Weighted distance maps computation on parametric three-dimensional manifolds, Journal of Computational Physics, Vol. 255(1), 2007 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Paretian similarity for partial comparison of non-rigid objects, Proc. Scale Space and Variational Methods in Computer Vision (SSVM), 2007 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Partial similarity of objects and text sequences, Proc. Information Theory and Applications Workshop, 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression-invariant representation of faces, IEEE Trans. Image Processing, Vol. 16(1), 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Story of Cinderella: biometrics and isometry-invariant distances, Chapter in 3D Imaging for Safety and Security (A. Koschan, M. Pollefeys, M. Abidi Eds.), Springer, 2007 detailsD. Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel, Symmetries of non-rigid shapes, Proc. Workshop on Non-rigid Registration and Tracking through Learning (NRTL), 2007 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Robust expression-invariant face recognition from partially missing data, Proc. European Conf. on Computer Vision (ECCV), 2006 detailsA. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, R. Kimmel, Matching two-dimensional articulated shapes using generalized multidimensional scaling, Proc. Conf. on Articulated Motion and Deformable Objects (AMDO), 2006 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Face2Face: an isometric model for facial animation, Proc. Conf. on Articulated Motion and Deformable Objects (AMDO), 2006 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Efficient computation of isometry-invariant distances between surfaces, SIAM J. Scientific Computing, Vol. 28(5), 2006A. M. Bronstein, M. M. Bronstein, M. Zibulevsky, On separation of semitransparent dynamic images from static background, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, 2006 detailsM. M. Bronstein, A. M. Bronstein, R. Kimmel, I. Yavneh, Multigrid multidimensional scaling, Numerical Linear Algebra with Applications (NLAA), Vol. 13(2), 2006 (Special issue on multigrid methods) detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Generalized multidimensional scaling: a framework for isometry-invariant partial surface matching, Proc. US National Academy of Sciences (PNAS), Vol. 103(5), 2006 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression invariant face recognition: faces as isometric surfaces, Chapter in Face Processing: Advanced Modeling and Methods (Rama Chellappa, Wenyi Zhao Eds.), Academic Press, 2006 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Three-dimensional face recognition, Int'l Journal of Computer Vision (IJCV), Vol. 64(1), 2005 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Quasi maximum likelihood blind deconvolution: super- an sub-Gaussianity versus consistency, IEEE Trans. Signal Processing, Vol. 53(7), 2005 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Relative optimization for blind deconvolution, IEEE Trans. on Signal Processing, Vol. 53(6), 2005 detailsM. M. Bronstein, A. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Blind deconvolution of images using optimal sparse representations, IEEE Trans. on Image Processing, Vol. 14(6), 2005 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression-invariant face recognition via spherical embedding, Proc. Int'l Conf. on Image Processing (ICIP), 2005 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Unmixing tissues: sparse component analysis in multi-contrast MRI, Proc. Int'l Conf. on Image Processing (ICIP), 2005 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Isometric embedding of facial surfaces into S^3, Proc. Int'l Conf. on Scale Space and PDE Methods in Computer Vision (SSVM), 2005 detailsM. M. Bronstein, A. M. Bronstein, R. Kimmel, I. Yavneh, A multigrid approach for multi-dimensional scaling, Proc. Copper Mountain Conf. Multigrid Methods, 2005 (Best Paper Award) detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Sparse ICA for blind separation of transmitted and reflected images, Int'l Journal of Imaging Science and Technology (IJIST), Vol. 15(1), 2005 detailsA. M. Bronstein, M. M. Bronstein, E. Gordon, R. Kimmel, Fusion of 2D and 3D data in three-dimensional face recognition, Proc. Int'l Conf. on Image Processing (ICIP), 2004 detailsM. M. Bronstein, A. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi,, Optimal sparse representations for blind source separation and blind deconvolution: a learning approach, Proc. Int'l Conf. on Image Processing (ICIP), 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Fast relative Newton algorithm for blind deconvolution of images, Proc. Int'l Conf. on Image Processing (ICIP), 2004 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, A. Spira, Face recognition from facial surface metric, Proc. European Conf. on Computer Vision (ECCV), 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Blind source separation using block-coordinate relative Newton method, Signal Processing, Vol. 84(8), 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Blind source separation using the block-coordinate relative Newton method, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, Lecture Notes in Comp. Science No. 3195, Springer, 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, QML blind deconvolution: asymptotic analysis, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Optimal sparse representations for blind deconvolution of images, Proc. Int'l Conf. on Independent Component Analysis and Blind Signal Separation, 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Quasi maximum likelihood blind deconvolution of images acquired through scattering media, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2004 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Optimal nonlinear line-of-flight estimation in positron emission tomography, IEEE Trans. on Nuclear Science, Vol. 50(3), 2003 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Separation of semireflective layers using Sparse ICA, Proc. Int'l Conf. on Acoustics Speech and Signal Processing (ICASSP), 2003 detailsA. M. Bronstein, M. M. Bronstein, R. Kimmel, Expression-invariant 3D face recognition, Proc. Audio- and Video-based Biometric Person Authentication (AVBPA), Lecture Notes in Comp. Science No. 2688, Springer, 2003 detailsM. M. Bronstein, A. M. Bronstein, Biometrics was no match for hair-raising tricks, Nature Vol. 420, 2002M. M. Bronstein, A. M. Bronstein, M. Zibulevsky, H. Azhari, Reconstruction in ultrasound diffraction tomography using non-uniform FFT, IEEE Trans. on Medical Imaging, Vol. 21(11), 2002 detailsM. M. Bronstein, A. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Iterative reconstruction in diffraction tomography using non-uniform fast Fourier transform, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2002 detailsA. M. Bronstein, M. M. Bronstein, M. Zibulevsky, Y. Y. Zeevi, Optimal nonlinear estimation of photon coordinates in PET, Proc. Int'l Symposium on Biomedical Imaging (ISBI), 2002 details