| 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 | 7153 | 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 | 4406 | 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 | 2396 | 2017 |
| Geometric deep learning: Grids, groups, graphs, geodesics, and gauges MM Bronstein, J Bruna, T Cohen, P Veličković arXiv preprint arXiv:2104.13478, 2021 | 1527 | 2021 |
| Numerical geometry of non-rigid shapes AM Bronstein, MM Bronstein, M Bronstein, R Kimmel Springer-Verlag New York Inc, 2008 | 995 | 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 | 993 | 2015 |
| 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 | 865 | 2018 |
| Temporal graph networks for deep learning on dynamic graphs E Rossi, B Chamberlain, F Frasca, D Eynard, F Monti, M Bronstein arXiv preprint arXiv:2006.10637, 2020 | 861 | 2020 |
| 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 | 843 | 2010 |
| Three-dimensional face recognition AM Bronstein, MM Bronstein, R Kimmel International Journal of Computer Vision 64, 5-30, 2005 | 763 | 2005 |
| 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 | 741 | 2012 |
| 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 | 736 | 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 | 727 | 2020 |
| 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 | 721 | 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 | 716 | 2011 |
| Geometric matrix completion with recurrent multi-graph neural networks F Monti, M Bronstein, X Bresson Advances in neural information processing systems 30, 2017 | 695 | 2017 |
| Learning shape correspondence with anisotropic convolutional neural networks D Boscaini, J Masci, E Rodolà, M Bronstein Advances in neural information processing systems 29, 2016 | 630 | 2016 |
| 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 | 573 | 2010 |
| Understanding over-squashing and bottlenecks on graphs via curvature J Topping, F Di Giovanni, BP Chamberlain, X Dong, MM Bronstein arXiv preprint arXiv:2111.14522, 2021 | 542 | 2021 |
| Improving graph neural network expressivity via subgraph isomorphism counting G Bouritsas, F Frasca, S Zafeiriou, MM Bronstein IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 657-668, 2022 | 537 | 2022 |
Alex BronsteinDan Broida Academic Chair, Schmidt Chair of AI, CS@Technion確認したメール アドレス: technion.ac.il