Michael M. Bronstein

发表

Hyperbolic Deep Reinforcement Learning

Jonathan J. Hunt, B. Chamberlain, Michael Bronstein, 2022, ICLR.

Structure-based Drug Design with Equivariant Diffusion Models

T. Blundell, B. Correia, Yuanqi Du, 2022, ArXiv.

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

F. Frasca, Haggai Maron, Michael Bronstein, 2022, NeurIPS.

Graph-based Representation Learning for Web-scale Recommender Systems

A. Haghighi, Ahmed El-Kishky, Ying Xiao, 2022, KDD.

Edge Directionality Improves Learning on Heterophilic Graphs

Stephan Günnemann, Francesco Di Giovanni, Stephan Günnemann, 2023, ArXiv.

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

Francesco Di Giovanni, B. Chamberlain, Michael Bronstein, 2022, NeurIPS.

Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Victor Garcia Satorras, P. Frossard, B. Correia, 2022, ArXiv.

De novo design of site-specific protein interactions with learned surface fingerprints

G. Gao, B. Fierz, Shuguang Tan, 2023, bioRxiv.

A Survey on Oversmoothing in Graph Neural Networks

T. Konstantin Rusch, Michael Bronstein, Siddhartha Mishra, 2023, ArXiv.

Structure-based Drug Design with Equivariant Diffusion Models

T. Blundell, B. Correia, Yuanqi Du, 2022, ArXiv.

Gradient Gating for Deep Multi-Rate Learning on Graphs

Michael W. Mahoney, T. Konstantin Rusch, B. Chamberlain, 2022, ICLR.

Decoding Surface Fingerprints for Protein-Ligand Interactions

T. Blundell, P. Lio’, Freyr Sverrisson, 2022, bioRxiv.

From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module

P. Lorenzo, Simone Scardapane, Indro Spinelli, 2023, 2305.16174.

DRew: Dynamically Rewired Message Passing with Delay

Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein, 2023, ICML.

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

Francesco Di Giovanni, Giulia Luise, Federico Barbero, 2023, ICML.

Graph Neural Networks as Gradient Flows

Francesco Di Giovanni, B. Chamberlain, J. Rowbottom, 2022, ArXiv.

Sheaf Neural Networks with Connection Laplacians

Haitz S'aez de Oc'ariz Borde, Petar Velivckovi'c, Michael Bronstein, 2022, ArXiv.

How does over-squashing affect the power of GNNs?

T. Konstantin Rusch, Francesco Di Giovanni, Petar Velivckovi'c, 2023, ArXiv.

Understanding convolution on graphs via energies

Francesco Di Giovanni, B. Chamberlain, J. Rowbottom, 2022, 2206.10991.

Curvature Filtrations for Graph Generative Model Evaluation

Bastian Alexander Rieck, Jeremy Wayland, Joshua Southern, 2023, ArXiv.

Graph Neural Networks for Link Prediction with Subgraph Sketching

Nils Y. Hammerla, N. Hammerla, B. Chamberlain, 2022, ICLR.

Temporal Graph Benchmark for Machine Learning on Temporal Graphs

J. Leskovec, Weihua Hu, Matthias Fey, 2023, ArXiv.

On the Impact of Sample Size in Reconstructing Graph Signals

Xiaowen Dong, Michael M. Bronstein, Baskaran Sripathmanathan, 2023, 2307.00336.

Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization

Ric De Santi, Marcello Restelli, Mirco Mutti, 2022, AAAI.

Interaction data are identifiable even across long periods of time

Y. de Montjoye, Federico Monti, Xiaowen Dong, 2022, Nature Communications.

Invariance Discovery for Systematic Generalization in Reinforcement Learning

Ric De Santi, Marcello Restelli, Mirco Mutti, 2022 .

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Connor W. Coley, Chaitanya K. Joshi, Aria Mansouri Tehrani, 2023, arXiv.org.

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications

N. Navab, L. Cosmo, Seyed-Ahmad Ahmadi, 2022, Medical Image Anal..

RetroBridge: Modeling Retrosynthesis with Markov Bridges

Marwin H. S. Segler, B. Correia, Ilia Igashov, 2023, ArXiv.

How does over-squashing affect the power of GNNs?

T. Konstantin Rusch, Francesco Di Giovanni, Petar Velivckovi'c, 2023, ArXiv.

Understanding convolution on graphs via energies

Francesco Di Giovanni, B. Chamberlain, J. Rowbottom, 2022, 2206.10991.

Locality-Aware Graph-Rewiring in GNNs

Francesco Di Giovanni, A. Velingker, Federico Barbero, 2023, ArXiv.

From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module

P. Lorenzo, Simone Scardapane, Indro Spinelli, 2023, ArXiv.

Edge Directionality Improves Learning on Heterophilic Graphs

Francesco Di Giovanni, Stephan Günnemann, Bertrand Charpentier, 2023, LoG.

Curvature Filtrations for Graph Generative Model Evaluation

Bastian Alexander Rieck, Jeremy Wayland, Joshua Southern, 2023, NeurIPS.

Learning to Infer Structures of Network Games

Federico Monti, Xiaowen Dong, Yan Leng, 2022, ICML.

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Connor W. Coley, Chaitanya K. Joshi, Aria Mansouri Tehrani, 2023, ArXiv.

Temporal Graph Benchmark for Machine Learning on Temporal Graphs

J. Leskovec, Weihua Hu, Matthias Fey, 2023, NeurIPS.