| Dynamic graph cnn for learning on point clouds Y Wang, Y Sun, Z Liu, SE Sarma, MM Bronstein, JM Solomon Acm Transactions On Graphics (tog) 38 (5), 1-12, 2019 | 3615 | 2019 |
| Geometric deep learning: going beyond euclidean data MM Bronstein, J Bruna, Y LeCun, A Szlam, P Vandergheynst IEEE Signal Processing Magazine 34 (4), 18-42, 2017 | 2947 | 2017 |
| Geometric deep learning on graphs and manifolds using mixture model cnns F Monti, D Boscaini, J Masci, E Rodola, J Svoboda, MM Bronstein Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1731 | 2017 |
| Numerical geometry of non-rigid shapes AM Bronstein, MM Bronstein, M Bronstein, R Kimmel Springer-Verlag New York Inc, 2008 | 875 | 2008 |
| Geodesic convolutional neural networks on riemannian manifolds J Masci, D Boscaini, M Bronstein, P Vandergheynst Proceedings of the IEEE international conference on computer vision …, 2015 | 797 | 2015 |
| Three-dimensional face recognition AM Bronstein, MM Bronstein, R Kimmel International Journal of Computer Vision 64, 5-30, 2005 | 749 | 2005 |
| Scale-invariant heat kernel signatures for non-rigid shape recognition MM Bronstein, I Kokkinos International Conference on Computer Vision and Pattern Recognition, 1704-1711, 2010 | 741* | 2010 |
| LDAHash: Improved matching with smaller descriptors C Strecha, AM Bronstein, MM Bronstein, P Fua Pattern Analysis and Machine Intelligence, IEEE Transactions on 34 (1), 66-78, 2012 | 707 | 2012 |
| Generalized multidimensional scaling: a framework for isometry-invariant partial surface matching AM Bronstein, MM Bronstein, R Kimmel Proceedings of the National Academy of Sciences of the United States of …, 2006 | 678 | 2006 |
| Shape google: Geometric words and expressions for invariant shape retrieval AM Bronstein, MM Bronstein, LJ Guibas, M Ovsjanikov ACM Transactions on Graphics (TOG) 30 (1), 1-20, 2011 | 675 | 2011 |
| Cayleynets: Graph convolutional neural networks with complex rational spectral filters R Levie, F Monti, X Bresson, MM Bronstein IEEE Transactions on Signal Processing 67 (1), 97-109, 2018 | 575 | 2018 |
| Learning shape correspondence with anisotropic convolutional neural networks D Boscaini, J Masci, E Rodolà, M Bronstein Advances in neural information processing systems 29, 2016 | 529 | 2016 |
| Geometric deep learning: Grids, groups, graphs, geodesics, and gauges MM Bronstein, J Bruna, T Cohen, P Veličković arXiv preprint arXiv:2104.13478, 2021 | 516 | 2021 |
| Geometric matrix completion with recurrent multi-graph neural networks F Monti, M Bronstein, X Bresson Advances in neural information processing systems 30, 2017 | 513 | 2017 |
| Data fusion through cross-modality metric learning using similarity-sensitive hashing MM Bronstein, AM Bronstein, F Michel, N Paragios 2010 IEEE computer society conference on computer vision and pattern …, 2010 | 501 | 2010 |
| Expression-invariant 3D face recognition AM Bronstein, MM Bronstein, R Kimmel Audio-and Video-Based Biometric Person Authentication, 62-70, 2003 | 423 | 2003 |
| Fake news detection on social media using geometric deep learning F Monti, F Frasca, D Eynard, D Mannion, MM Bronstein arXiv preprint arXiv:1902.06673, 2019 | 392 | 2019 |
| Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning P Gainza, F Sverrisson, F Monti, E Rodola, D Boscaini, MM Bronstein, ... Nature Methods 17 (2), 184-192, 2020 | 342 | 2020 |
| A Gromov-Hausdorff framework with diffusion geometry for topologically-robust non-rigid shape matching AM Bronstein, MM Bronstein, R Kimmel, M Mahmoudi, G Sapiro International Journal of Computer Vision 89 (2-3), 266-286, 2010 | 335 | 2010 |
| Efficient computation of isometry-invariant distances between surfaces AM Bronstein, MM Bronstein, R Kimmel SIAM Journal on Scientific Computing 28 (5), 1812-1836, 2006 | 298 | 2006 |
Alex BronsteinTechnion, Department of Computer Science在 technion.ac.il 的电子邮件经过验证
