Michael M. Bronstein
39 papers · 2015–2025 · 4 conferences · across top CS/AI conferences
Achievements
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(32)
π§
Keyword Pioneer
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Topic Evolution
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Triple Crown
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Keyword Champion
(2)
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Mega-Team
(22)
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(7)
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Prolific Year
(9)
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Trend Setter
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Century Club
(39)
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The Questioner
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Keyword Collector
(70)
Conferences
ICLR (17)
ICML (13)
CVPR (8)
NIPS (1)
Top co-authors
Keywords
shape matching
(3)
graph neural network
(3)
geometric deep learning
(3)
point cloud
(2)
graph rewiring
(2)
shape reconstruction
(2)
non-rigid deformation
(2)
shape correspondence
(1)
style transfer
(1)
feature learning
(1)
hand pose estimation
(1)
weak supervision
(1)
topological data analysis
(1)
neural network optimization
(1)
3d vision
(1)
graph classification
(1)
dense correspondence
(1)
message passing
(1)
gradient-based method
(1)
global optimization
(1)
Papers
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
ICML 2025
Homomorphism Counts as Structural Encodings for Graph Learning
ICLR 2025
Multi-domain Distribution Learning for De Novo Drug Design
ICLR 2025
Neural Spacetimes for DAG Representation Learning
ICLR 2025
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity
ICLR 2025
Bundle Neural Network for message diffusion on graphs
ICLR 2025
Fully-inductive Node Classification on Arbitrary Graphs
ICLR 2025
Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity
ICLR 2025
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction
ICLR 2025
On Measuring Long-Range Interactions in Graph Neural Networks
ICML 2025
How Expressive are Knowledge Graph Foundation Models?
ICML 2025
A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition
ICML 2025
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
ICML 2025
Scalable Equilibrium Sampling with Sequential Boltzmann Generators
ICML 2025
Supercharging Graph Transformers with Advective Diffusion
ICML 2025
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
ICLR 2024
SE(3)-Stochastic Flow Matching for Protein Backbone Generation
ICLR 2024
RetroBridge: Modeling Retrosynthesis with Markov Bridges
ICLR 2024
On the Limitations of Fractal Dimension as a Measure of Generalization
NIPS 2024
Cooperative Graph Neural Networks
ICML 2024
Homomorphism Counts for Graph Neural Networks: All About That Basis
ICML 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
Locality-Aware Graph Rewiring in GNNs
ICLR 2024
Hyperbolic Deep Reinforcement Learning
ICLR 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
ICML 2023
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
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
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild
CVPR 2020
Geometrically Principled Connections in Graph Neural Networks
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