Publications Peer reviewed articles (8) Geometric Deep Learning: Going beyond Euclidean data Author(s): Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst Published in: IEEE Signal Processing Magazine, Issue 34/4, 2017, Page(s) 18-42, ISSN 1053-5888 Publisher: Institute of Electrical and Electronics Engineers DOI: 10.1109/msp.2017.2693418 Interactive curve constrained functional maps Author(s): A. Gehre, M. M. Bronstein, L. Kobbelt, J. Solomon Published in: Computer Graphics Forum, 2018, ISSN 1467-8659 Publisher: Wiley DOI: 10.1111/cgf.13486 Kernel functional maps Author(s): L. Wang, A. Gehre, M. M. Bronstein, J. Solomon Published in: Computer Graphics Forum, 2018, ISSN 1467-8659 Publisher: Wiley DOI: 10.1111/cgf.13488 Improved Functional Mappings via Product Preservation Author(s): D. Nogneng, S. Melzi, E. Rodolà, U. Castellani, M. Bronstein, M. Ovsjanikov Published in: Computer Graphics Forum, Issue 37/2, 2018, Page(s) 179-190, ISSN 0167-7055 Publisher: Blackwell Publishing Inc. DOI: 10.1111/cgf.13352 Functional Maps Representation On Product Manifolds Author(s): E. Rodolà, Z. Lähner, A. M. Bronstein, M. M. Bronstein, J. Solomon Published in: Computer Graphics Forum, Issue 38/1, 2018, Page(s) 678-689, ISSN 0167-7055 Publisher: Blackwell Publishing Inc. DOI: 10.1111/cgf.13598 CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters Author(s): Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein Published in: IEEE Transactions on Signal Processing, Issue 67/1, 2019, Page(s) 97-109, ISSN 1053-587X Publisher: Institute of Electrical and Electronics Engineers DOI: 10.1109/tsp.2018.2879624 Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning Author(s): P. Gainza, F. Sverrisson, F. Monti, E. Rodolà, D. Boscaini, M. M. Bronstein, B. E. Correia Published in: Nature Methods, 2020, ISSN 1548-7091 Publisher: Nature Publishing Group DOI: 10.1038/s41592-019-0666-6 Using attribution to decode binding mechanism in neural network models for chemistry Author(s): Kevin McCloskey, Ankur Taly, Federico Monti, Michael P. Brenner, Lucy J. Colwell Published in: Proceedings of the National Academy of Sciences, 2018, Page(s) 201820657, ISSN 0027-8424 Publisher: National Academy of Sciences DOI: 10.1073/pnas.1820657116 Conference proceedings (10) Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs Author(s): Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodola, Jan Svoboda, Michael M. Bronstein Published in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Page(s) 5425-5434, ISBN 978-1-5386-0457-1 Publisher: IEEE DOI: 10.1109/cvpr.2017.576 Geometric matrix completion with recurrent multi-graph neural networks Author(s): F. Monti, M. M. Bronstein, X. Bresson Published in: Neural Information Processing Systems, 2017 Publisher: NIPS Efficient Deformable Shape Correspondence via Kernel Matching Author(s): Matthias Vestner, Zorah Lahner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodola, Alex Bronstein, Michael Bronstein, Ron Kimmel, Daniel Cremers Published in: 2017 International Conference on 3D Vision (3DV), 2017, Page(s) 517-526, ISBN 978-1-5386-2610-8 Publisher: IEEE DOI: 10.1109/3dv.2017.00065 Deep Functional Maps: Structured Prediction for Dense Shape Correspondence Author(s): Or Litany, Tal Remez, Emanuele Rodola, Alex Bronstein, Michael Bronstein Published in: 2017 IEEE International Conference on Computer Vision (ICCV), 2017, Page(s) 5660-5668, ISBN 978-1-5386-1032-9 Publisher: IEEE DOI: 10.1109/iccv.2017.603 MOTIFNET: A MOTIF-BASED GRAPH CONVOLUTIONAL NETWORK FOR DIRECTED GRAPHS Author(s): Federico Monti, Karl Otness, Michael M. Bronstein Published in: 2018 IEEE Data Science Workshop (DSW), 2018, Page(s) 225-228, ISBN 978-1-5386-4410-2 Publisher: IEEE DOI: 10.1109/dsw.2018.8439897 Graph Neural Networks for IceCube Signal Classification Author(s): Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat Prabhat, Wahid Bhimji, Michael Bronstein, Spencer Klein, Joan Bruna Published in: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018, Page(s) 386-391, ISBN 978-1-5386-6805-4 Publisher: IEEE DOI: 10.1109/icmla.2018.00064 Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks Author(s): Monti, Federico; Bronstein, Michael M.; Bresson, Xavier Published in: NIPS, Issue 7, 2017 Publisher: Nips PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks Author(s): Svoboda, Jan; Masci, Jonathan; Monti, Federico; Bronstein, Michael M.; Guibas, Leonidas Published in: ICLR, Issue 7, 2019 Publisher: ICLR Partition and Code: Learning how to compress graphs Author(s): Giorgos Bouritsas; Loukas, A.; Karalias, N.; Bronstein, M. M. Published in: Neurips, Issue 1, 2021 Publisher: Neurips DOI: 10.48550/arxiv.2107.01952 GRAND: Graph Neural Diffusion Author(s): Chamberlain, Benjamin Paul; Rowbottom, James; Gorinova, Maria; Webb, Stefan; Rossi, Emanuele; Bronstein, Michael M. Published in: ICML, Issue 9, 2021 Publisher: ICML DOI: 10.48550/arxiv.2106.10934 Other (2) Fake News Detection on Social Media using Geometric Deep Learning Author(s): Monti, Federico; Frasca, Fabrizio; Eynard, Davide; Mannion, Damon; Bronstein, Michael M. Published in: Issue 2, 2019 Publisher: arxiv Dual-Primal Graph Convolutional Networks Author(s): Monti, Federico; Shchur, Oleksandr; Bojchevski, Aleksandar; Litany, Or; Günnemann, Stephan; Bronstein, Michael M. Published in: Issue 5, 2018 Publisher: arxiv Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
