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Michael Bronstein
Michael Bronstein
DeepMind Professor of AI, University of Oxford / Head Graph ML Research, Twitter
Verified email at cs.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
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
26662019
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
24542017
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
14632017
Numerical geometry of non-rigid shapes
AM Bronstein, MM Bronstein, M Bronstein, R Kimmel
Springer-Verlag New York Inc, 2008
8382008
Three-dimensional face recognition
AM Bronstein, MM Bronstein, R Kimmel
International Journal of Computer Vision 64 (1), 5-30, 2005
7412005
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
7122015
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
708*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
6862012
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
6692006
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
6562011
Learning shape correspondence with anisotropic convolutional neural networks
D Boscaini, J Masci, E Rodolà, M Bronstein
Advances in neural information processing systems 29, 2016
4792016
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
4752010
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
4632018
Geometric matrix completion with recurrent multi-graph neural networks
F Monti, M Bronstein, X Bresson
Advances in neural information processing systems 30, 2017
4382017
Expression-invariant 3D face recognition
AM Bronstein, MM Bronstein, R Kimmel
Audio-and Video-Based Biometric Person Authentication, 62-70, 2003
4232003
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), 266-286, 2010
3272010
Efficient computation of isometry-invariant distances between surfaces
AM Bronstein, MM Bronstein, R Kimmel
SIAM Journal on Scientific Computing 28 (5), 1812-1836, 2006
2902006
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
2872019
Geometric deep learning: Grids, groups, graphs, geodesics, and gauges
MM Bronstein, J Bruna, T Cohen, P Veličković
arXiv preprint arXiv:2104.13478, 2021
2582021
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
2422020
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