Michael M. Bronstein

A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition ICML 2025 Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality ICML 2025 Bundle Neural Network for message diffusion on graphs ICLR 2025 Fully-inductive Node Classification on Arbitrary Graphs ICLR 2025 Homomorphism Counts as Structural Encodings for Graph Learning ICLR 2025 How Expressive are Knowledge Graph Foundation Models? ICML 2025 Multi-domain Distribution Learning for De Novo Drug Design ICLR 2025 Neural Spacetimes for DAG Representation Learning ICLR 2025 On Measuring Long-Range Interactions in Graph Neural Networks ICML 2025 Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks ICML 2025 Scalable Equilibrium Sampling with Sequential Boltzmann Generators ICML 2025 Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction ICLR 2025 Supercharging Graph Transformers with Advective Diffusion ICML 2025 Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity ICLR 2025 Understanding Virtual Nodes: Oversquashing and Node Heterogeneity ICLR 2025 Cooperative Graph Neural Networks ICML 2024 From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module ICLR 2024 Homomorphism Counts for Graph Neural Networks: All About That Basis ICML 2024 Locality-Aware Graph Rewiring in GNNs ICLR 2024 On the Limitations of Fractal Dimension as a Measure of Generalization NeurIPS 2024 Position: Future Directions in the Theory of Graph Machine Learning ICML 2024 Position: Topological Deep Learning is the New Frontier for Relational Learning ICML 2024 RetroBridge: Modeling Retrosynthesis with Markov Bridges ICLR 2024 SE(3)-Stochastic Flow Matching for Protein Backbone Generation ICLR 2024 DRew: Dynamically Rewired Message Passing with Delay ICML 2023 Gradient Gating for Deep Multi-Rate Learning on Graphs ICLR 2023 Graph Neural Networks for Link Prediction with Subgraph Sketching ICLR 2023 Hyperbolic Deep Reinforcement Learning ICLR 2023 On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology ICML 2023 Equivariant Subgraph Aggregation Networks ICLR 2022 Understanding over-squashing and bottlenecks on graphs via curvature ICLR 2022 Fast End-to-End Learning on Protein Surfaces CVPR 2021 Geometrically Principled Connections in Graph Neural Networks CVPR 2020 Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild CVPR 2020 GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching CVPR 2019 Isospectralization, or How to Hear Shape, Style, and Correspondence CVPR 2019 Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs CVPR 2017 Efficient Globally Optimal 2D-To-3D Deformable Shape Matching CVPR 2016 Functional Correspondence by Matrix Completion CVPR 2015