Deep LEarning on MANifolds and graphs

Project Information

LEMAN

Grant agreement ID: 724228

DOI

10.3030/724228

Project closed

EC signature date 15 December 2016

Start date 1 October 2017

End date 30 September 2023

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 997 875,00

EU contribution

€ 1 997 875,00

Coordinated by

THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
United Kingdom

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Book chapters (2)

Unsupervised Diffeomorphic Surface Registration and Non-linear Modelling

Author(s): Balder Croquet, Daan Christiaens, Seth M. Weinberg, Michael Bronstein, Dirk Vandermeulen, Peter Claes
Published in: Lecture Notes in Computer Science, Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 2021, Page(s) 118-128
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-87202-1_12

The Average Mixing Kernel Signature

Author(s): Luca Cosmo, Giorgia Minello, Michael Bronstein, Luca Rossi, Andrea Torsello
Published in: Lecture Notes in Computer Science, Computer Vision – ECCV 2020, 2021, Page(s) 1-17
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-58565-5_1

Conference proceedings (24)

Geometrically Principled Connections in Graph Neural Networks

Author(s): Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou
Published in: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Issue 31, 2022, Page(s) 11412-11421
Publisher: IEEE
DOI: 10.1109/cvpr42600.2020.01143

Beltrami Flow and Neural Diffusion on Graphs

Author(s): Chamberlain, BP; Rowbottom, J; Eynard, D; Di Giovanni, F; Dong, X; Bronstein, MM
Published in: NeurIPS, 2021
Publisher: neurips
DOI: 10.48550/arxiv.2110.09443

Understanding over-squashing and bottlenecks on graphs via curvature

Author(s): Topping, J; Di Giovanni, F; Chamberlain, BP; Dong, X; Bronstein, M
Published in: ICLR, 2022
Publisher: ICLR
DOI: 10.48550/arxiv.2111.14522

PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks

Author(s): Svoboda, Jan; Masci, Jonathan; Monti, Federico; Bronstein, Michael M.; Guibas, Leonidas
Published in: ICLR, Issue 6, 2019
Publisher: ICLR

Edge Directionality Improves Learning on Heterophilic Graphs

Author(s): Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael Bronstein
Published in: LoG, 2023
Publisher: log

Gradient Gating for Deep Multi-Rate Learning on Graphs

Author(s): Rusch, T. Konstantin; Chamberlain, Benjamin P.; Mahoney, Michael W.; Bronstein, Michael; Mishra, Siddhartha
Published in: ICML, 2023
Publisher: icml
DOI: 10.48550/arxiv.2210.00513

DRew: Dynamically Rewired Message Passing with Delay

Author(s): Benjamin Gutteridge, Xiaowen Dong, Michael Bronstein, Francesco Di Giovanni
Published in: ICML, 2023
Publisher: icml

Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs

Author(s): Bodnar, C; Di Giovanni, F; Chamberlain, BP; Liò, P; Bronstein, M
Published in: NeurIPS, 2022
Publisher: neurips
DOI: 10.48550/arxiv.2202.04579

On Over-Squashing in Message Passing Neural Networks:The Impact of Width, Depth, and Topology

Author(s): Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael Bronstein
Published in: ICML, 2023
Publisher: icml

SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator

Author(s): Shunwang Gong, Lei Chen, Michael Bronstein, Stefanos Zafeiriou
Published in: 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2022
Publisher: IEEE
DOI: 10.1109/iccvw.2019.00509

Weisfeiler and Lehman Go Cellular: CW Networks

Author(s): Bodnar, Cristian; Frasca, Fabrizio; Otter, Nina; Wang, Yu Guang; Liò, Pietro; Montúfar, Guido; Bronstein, Michael
Published in: NeurIPS, 2021
Publisher: neurips
DOI: 10.48550/arxiv.2106.12575

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

Graph Neural Networks for Link Prediction with Subgraph Sketching

Author(s): Chamberlain, Benjamin Paul; Shirobokov, Sergey; Rossi, Emanuele; Frasca, Fabrizio; Markovich, Thomas; Hammerla, Nils; Bronstein, Michael M.; Hansmire, Max
Published in: ICLR, Issue 7, 2023
Publisher: icml
DOI: 10.48550/arxiv.2209.15486

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

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

Author(s): Frasca, F; Bevilacqua, B; Bronstein, M; Maron, H
Published in: NeurIPS, 2022
Publisher: Neurips
DOI: 10.48550/arxiv.2206.11140

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

Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation

Author(s): Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Stefanos Zafeiriou, Michael Bronstein
Published in: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2022
Publisher: IEEE
DOI: 10.1109/iccv.2019.00731

Equivariant Subgraph Aggregation Networks

Author(s): Bevilacqua, Beatrice; Frasca, Fabrizio; Lim, Derek; Srinivasan, Balasubramaniam; Cai, Chen; Balamurugan, Gopinath; Bronstein, Michael M.; Maron, Haggai
Published in: ICLR, 2022
Publisher: iclr
DOI: 10.48550/arxiv.2110.02910

Peer reviewed articles (18)

Nonisometric Surface Registration via Conformal Laplace–Beltrami Basis Pursuit

Author(s): Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai
Published in: Journal of Scientific Computing, Issue 86, 2021, ISSN 0885-7474
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10915-020-01390-y

Predicting anticancer hyperfoods with graph convolutional networks

Author(s): Guadalupe Gonzalez, Shunwang Gong, Ivan Laponogov, Michael Bronstein, Kirill Veselkov
Published in: Human Genomics, Issue 15, 2023, ISSN 1479-7364
Publisher: Springer Nature
DOI: 10.1186/s40246-021-00333-4

Alzheimer’s disease: using gene/protein network machine learning for molecule discovery in olive oil

Author(s): Luís Rita, Natalie R. Neumann, Ivan Laponogov, Guadalupe Gonzalez, Dennis Veselkov, Domenico Pratico, Reza Aalizadeh, Nikolaos S. Thomaidis, David C. Thompson, Vasilis Vasiliou, Kirill Veselkov
Published in: Human Genomics, Issue 17, 2023, ISSN 1479-7364
Publisher: Springer Nature
DOI: 10.1186/s40246-023-00503-6

Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

Author(s): Alexander A. Aksenov, Ivan Laponogov, Zheng Zhang, Sophie L. F. Doran, Ilaria Belluomo, Dennis Veselkov, Wout Bittremieux, Louis Felix Nothias, Mélissa Nothias-Esposito, Katherine N. Maloney, Biswapriya B. Misra, Alexey V. Melnik, Aleksandr Smirnov, Xiuxia Du, Kenneth L. Jones, Kathleen Dorrestein, Morgan Panitchpakdi, Madeleine Ernst, Justin J. J. van der Hooft, Mabel Gonzalez, Chiara Carazzone,
Published in: Nature Biotechnology, Issue 39, 2023, Page(s) 169-173, ISSN 1087-0156
Publisher: Nature Publishing Group
DOI: 10.1038/s41587-020-0700-3

Differentiable Graph Module (DGM) for Graph Convolutional Networks

Author(s): Anees Kazi, Luca Cosmo, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence, Issue 45, 2023, Page(s) 1606-1617, ISSN 0162-8828
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2022.3170249

De novo design of protein interactions with learned surface fingerprints

Author(s): Pablo Gainza, Sarah Wehrle, Alexandra Van Hall-Beauvais, Anthony Marchand, Andreas Scheck, Zander Harteveld, Stephen Buckley, Dongchun Ni, Shuguang Tan, Freyr Sverrisson, Casper Goverde, Priscilla Turelli, Charlène Raclot, Alexandra Teslenko, Martin Pacesa, Stéphane Rosset, Sandrine Georgeon, Jane Marsden, Aaron Petruzzella, Kefang Liu, Zepeng Xu, Yan Chai, Pu Han, George F. Gao, Elisa Oricchio,
Published in: Nature, Issue 617, 2023, Page(s) 176-184, ISSN 0028-0836
Publisher: Nature Publishing Group
DOI: 10.1038/s41586-023-05993-x

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

Network machine learning maps phytochemically rich “Hyperfoods” to fight COVID-19

Author(s): Ivan Laponogov, Guadalupe Gonzalez, Madelen Shepherd, Ahad Qureshi, Dennis Veselkov, Georgia Charkoftaki, Vasilis Vasiliou, Jozef Youssef, Reza Mirnezami, Michael Bronstein, Kirill Veselkov
Published in: Human Genomics, Issue 15, 2024, ISSN 1479-7364
Publisher: Springer Media
DOI: 10.1186/s40246-020-00297-x

HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods

Author(s): Kirill Veselkov, Guadalupe Gonzalez, Shahad Aljifri, Dieter Galea, Reza Mirnezami, Jozef Youssef, Michael Bronstein, Ivan Laponogov
Published in: Scientific Reports, Issue 9, 2022, ISSN 2045-2322
Publisher: Nature Publishing Group
DOI: 10.1038/s41598-019-45349-y

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

Author(s): Mehdi Bahri, Eimear O’ Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou
Published in: International Journal of Computer Vision, Issue 129, 2023, Page(s) 2680-2713, ISSN 0920-5691
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s11263-021-01494-4

Genomic-driven nutritional interventions for radiotherapy-resistant rectal cancer patient

Author(s): Joshua Southern, Guadalupe Gonzalez, Pia Borgas, Liam Poynter, Ivan Laponogov, Yoyo Zhong, Reza Mirnezami, Dennis Veselkov, Michael Bronstein, Kirill Veselkov
Published in: Scientific Reports, Issue 13, 2023, ISSN 2045-2322
Publisher: Nature Publishing Group
DOI: 10.1038/s41598-023-41833-8

Other (9)

Learning Interpretable Disease Self-Representations for Drug Repositioning

Author(s): Frasca, F; Galeano, D; Gonzalez, G; Laponogov, I; Veselkov, K; Paccanaro, A; Bronstein, MM
Published in: arxiv, Issue 21, 2019
Publisher: arxiv
DOI: 10.48550/arxiv.1909.06609

Decoding Surface Fingerprints for Protein-Ligand Interactions

Author(s): Ilia Igashov, Arian R. Jamasb, Ahmed Sadek, Freyr Sverrisson, Arne Schneuing, Pietro Liò, Tom L. Blundell, Michael Bronstein, Bruno Correia
Published in: bioarxiv, 2022
Publisher: Cold Spring Harbor Laboratory
DOI: 10.1101/2022.04.26.489341

Unsupervised Network Embedding Beyond Homophily

Author(s): Zhong, Zhiqiang; Gonzalez, Guadalupe; Grattarola, Daniele; Pang, Jun
Published in: arxiv, 2022
Publisher: arxiv
DOI: 10.48550/arxiv.2203.10866

Combinatorial prediction of therapeutic perturbationsusing causally-inspired neural networks

Author(s): Guadalupe Gonzalez, Isuru Herath, Kirill Veselkov, Michael Bronstein, Marinka Zitnik
Published in: bioarxiv, 2024
Publisher: bioarxiv

Structure-based Drug Design with Equivariant Diffusion Models

Author(s): Schneuing, Arne; Du, Yuanqi; Harris, Charles; Jamasb, Arian; Igashov, Ilia; Du, Weitao; Blundell, Tom; Lió, Pietro; Gomes, Carla; Welling, Max; Bronstein, Michael; Correia, Bruno
Published in: bioarxiv, 2022
Publisher: bioarxiv
DOI: 10.48550/arxiv.2210.13695

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: arxiv, Issue 10, 2019
Publisher: arxiv
DOI: 10.48550/arxiv.1902.06673

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

Heterogeneous manifolds for curvature-aware graph embedding

Author(s): Di Giovanni, Francesco; Luise, Giulia; Bronstein, Michael
Published in: arxiv, 2022
Publisher: arxiv
DOI: 10.48550/arxiv.2202.01185

Intellectual Property Rights

Patent (1)

System and a method for learning features on geometric domains

Application/Publication number: us 10210430
Date: 2016-01-22
Applicant(s): UNIVERSITA DELLA SVIZZERA ITALIANA