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GRAND: Graph Neural Diffusion


Jun 21, 2021
Benjamin Paul Chamberlain, James Rowbottom, Maria Gorinova, Stefan Webb, Emanuele Rossi, Michael M. Bronstein

* 15 pages, 4 figures. Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021. Copyright 2021 by the author(s) 

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Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges


May 02, 2021
Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Veličković

* 156 pages. Work in progress -- comments welcome! 

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Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales


Apr 17, 2021
Jacob Andreas, Gašper Beguš, Michael M. Bronstein, Roee Diamant, Denley Delaney, Shane Gero, Shafi Goldwasser, David F. Gruber, Sarah de Haas, Peter Malkin, Roger Payne, Giovanni Petri, Daniela Rus, Pratyusha Sharma, Dan Tchernov, Pernille Tønnesen, Antonio Torralba, Daniel Vogt, Robert J. Wood


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Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation


Dec 16, 2020
Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou

* In review with International Journal of Computer Vision (IJCV) 

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Utilising Graph Machine Learning within Drug Discovery and Development


Dec 09, 2020
Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King

* 19 pages, 8 figures 

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Tuning Word2vec for Large Scale Recommendation Systems


Sep 24, 2020
Benjamin P. Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein

* Fourteenth ACM Conference on Recommender Systems (RecSys '20), September 22--26, 2020, Virtual Event, Brazil 
* 11 pages, 4 figures, Fourteenth ACM Conference on Recommender Systems 

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Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting


Jun 16, 2020
Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein


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Geometrically Principled Connections in Graph Neural Networks


Apr 06, 2020
Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou

* Presented at Computer Vision and Pattern Recognition (CVPR), 2020 

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Learning Interpretable Disease Self-Representations for Drug Repositioning


Oct 20, 2019
Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill Veselkov, Alberto Paccanaro, Michael M. Bronstein

* 10 pages, 2 figures, v2 corresponds to the camera ready version accepted at the Graph Representation Learning Workshop, NeurIPS 2019 

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Learning interpretable disease self-representations for drug repositioning


Sep 14, 2019
Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill Veselkov, Alberto Paccanaro, Michael M. Bronstein

* 10 pages, 2 figures 

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Transferability of Spectral Graph Convolutional Neural Networks


Jul 30, 2019
Ron Levie, Michael M. Bronstein, Gitta Kutyniok


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Fake News Detection on Social Media using Geometric Deep Learning


Feb 10, 2019
Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein


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Isospectralization, or how to hear shape, style, and correspondence


Nov 28, 2018
Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele RodolĂ 


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CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters


Oct 31, 2018
Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein


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Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit


Sep 19, 2018
Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai

* 21 pages, 7 figures 

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Graph Neural Networks for IceCube Signal Classification


Sep 17, 2018
Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna


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Geodesic convolutional neural networks on Riemannian manifolds


Jun 08, 2018
Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst


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Dual-Primal Graph Convolutional Networks


Jun 03, 2018
Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan GĂĽnnemann, Michael M. Bronstein


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PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks


May 31, 2018
Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas Guibas


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MotifNet: a motif-based Graph Convolutional Network for directed graphs


Feb 04, 2018
Federico Monti, Karl Otness, Michael M. Bronstein


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Dynamic Graph CNN for Learning on Point Clouds


Jan 24, 2018
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon


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Deep Functional Maps: Structured Prediction for Dense Shape Correspondence


Jul 30, 2017
Or Litany, Tal Remez, Emanuele RodolĂ , Alex M. Bronstein, Michael M. Bronstein

* Accepted for publication at ICCV 2017 

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Generative Convolutional Networks for Latent Fingerprint Reconstruction


May 04, 2017
Jan Svoboda, Federico Monti, Michael M. Bronstein


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Geometric deep learning: going beyond Euclidean data


May 03, 2017
Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst


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Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks


Apr 22, 2017
Federico Monti, Michael M. Bronstein, Xavier Bresson


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Geometric deep learning on graphs and manifolds using mixture model CNNs


Dec 06, 2016
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele RodolĂ , Jan Svoboda, Michael M. Bronstein


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Learning shape correspondence with anisotropic convolutional neural networks


May 20, 2016
Davide Boscaini, Jonathan Masci, Emanuele RodolĂ , Michael M. Bronstein


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Efficient Globally Optimal 2D-to-3D Deformable Shape Matching


Apr 11, 2016
Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers

* to appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016 

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Partial Functional Correspondence


Dec 22, 2015
Emanuele RodolĂ , Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers


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