Michael M. Bronstein

454 papers A* 66A 6B 8C 1Misc 2Journal 263Unranked 91
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Survey on Over-smoothing and Over-squashing: Unified Propagation Perspectives on Graph Neural Networks and Transformers.
Trans. Mach. Learn. Res.
Alvaro Arroyo, Federico Barbero, Hugh Blayney, Michael M. Bronstein, Xiaowen Dong, Pietro Lio, Razvan Pascanu, Pierre Vandergheynst
2026 J jnl
Can Graph Foundation Models Generalize Over Architecture?
CoRR
Benjamin Gutteridge, Michael M. Bronstein, Xiaowen Dong
2026 J jnl
Categorical Flow Maps.
CoRR
Daan Roos, Oscar Davis, Floor Eijkelboom, Michael M. Bronstein, Max Welling, Ismail Ilkan Ceylan, Luca Ambrogioni, Jan-Willem van de Meent
2026 J jnl
MacroGuide: Topological Guidance for Macrocycle Generation.
CoRR
Alicja Maksymiuk, Alexandre Duplessis, Michael M. Bronstein, Alexander Tong, Fernanda Duarte, Ismail Ilkan Ceylan
2026 J jnl
Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute.
CoRR
Kieran Didi, Zuobai Zhang, Guoqing Zhou, Danny Reidenbach, Zhonglin Cao, Sooyoung Cha, Tomas Geffner, Christian Dallago, Jian Tang, Michael M. Bronstein, Martin Steinegger, Emine Küçükbenli, Arash Vahdat, Karsten Kreis
2025 J jnl
A 3D Clinical Face Phenotype Space of Genetic Syndromes Using a Triplet-Based Singular Geometric Autoencoder.
IEEE Access
Soha Sadat Mahdi, Eduarda Caldeira, Harold S. Matthews, Michiel Vanneste, Nele Nauwelaers, Meng Yuan, Giorgos Bouritsas, Gareth S. Baynam, Peter Hammond, Richard A. Spritz, Ophir D. Klein, Michael M. Bronstein, Benedikt Hallgrímsson, Hilde Peeters, Peter Claes
2025 A* conf
A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition.
ICML
Nian Liu, Xiaoxin He, Thomas Laurent, Francesco Di Giovanni, Michael M. Bronstein, Xavier Bresson
2025 J jnl
Amortized Sampling with Transferable Normalizing Flows.
CoRR
Charlie B. Tan, Majdi Hassan, Leon Klein, Saifuddin Syed, Dominique Beaini, Michael M. Bronstein, Alexander Tong, Kirill Neklyudov
2025 J jnl
Are Large Language Models Good Temporal Graph Learners?
CoRR
Shenyang Huang, Ali Parviz, Emma Kondrup, Zachary Yang, Zifeng Ding, Michael M. Bronstein, Reihaneh Rabbany, Guillaume Rabusseau
2025 J jnl
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
Found. Trends Mach. Learn.
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2025 J jnl
Attention Sinks and Compression Valleys in LLMs are Two Sides of the Same Coin.
CoRR
Enrique Queipo-de-Llano, Alvaro Arroyo, Federico Barbero, Xiaowen Dong, Michael M. Bronstein, Yann LeCun, Ravid Shwartz-Ziv
2025 A* conf
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality.
ICML
Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca
2025 J jnl
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality.
CoRR
Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca
2025 A* conf
Bundle Neural Network for message diffusion on graphs.
ICLR
Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein
2025 J jnl
Carré du champ flow matching: better quality-generalisation tradeoff in generative models.
CoRR
Jacob Bamberger, Iolo Jones, Dennis Duncan, Michael M. Bronstein, Pierre Vandergheynst, Adam Gosztolai
2025 J jnl
CrediBench: Building Web-Scale Network Datasets for Information Integrity.
CoRR
Emma Kondrup, Sebastian Sabry, Hussein Abdallah, Zachary Yang, James Zhou, Kellin Pelrine, Jean-François Godbout, Michael M. Bronstein, Reihaneh Rabbany, Shenyang Huang
2025 J jnl
Curly Flow Matching for Learning Non-gradient Field Dynamics.
CoRR
Katarina Petrovic, Lazar Atanackovic, Viggo Moro, Kacper Kapusniak, Ismail Ilkan Ceylan, Michael M. Bronstein, Avishek Joey Bose, Alexander Tong
2025 J jnl
Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights.
CoRR
Zhiyuan Liang, Dongwen Tang, Yuhao Zhou, Xuanlei Zhao, Mingjia Shi, Wangbo Zhao, Zekai Li, Peihao Wang, Konstantin Schürholt, Damian Borth, Michael M. Bronstein, Yang You, Zhangyang Wang, Kai Wang
2025 J jnl
DyGMamba: Efficiently Modeling Long-Term Temporal Dependency on Continuous-Time Dynamic Graphs with State Space Models.
Trans. Mach. Learn. Res.
Zifeng Ding, Yifeng Li, Yuan He, Antonio Norelli, Jingcheng Wu, Volker Tresp, Michael M. Bronstein, Yunpu Ma
2025 J jnl
Efficient Learning on Large Graphs using a Densifying Regularity Lemma.
CoRR
Jonathan Kouchly, Ben Finkelshtein, Michael M. Bronstein, Ron Levie
2025 J jnl
Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models.
CoRR
Ben Finkelshtein, Ismail Ilkan Ceylan, Michael M. Bronstein, Ron Levie
2025 J jnl
FORT: Forward-Only Regression Training of Normalizing Flows.
CoRR
Danyal Rehman, Oscar Davis, Jiarui Lu, Jian Tang, Michael M. Bronstein, Yoshua Bengio, Alexander Tong, Avishek Joey Bose
2025 J jnl
Flock: A Knowledge Graph Foundation Model via Learning on Random Walks.
CoRR
Jinwoo Kim, Xingyue Huang, Krzysztof Olejniczak, Kyungbin Min, Michael M. Bronstein, Seunghoon Hong, Ismail Ilkan Ceylan
2025 J jnl
Flow-Based Fragment Identification via Binding Site-Specific Latent Representations.
CoRR
Rebecca M. Neeser, Ilia Igashov, Arne Schneuing, Michael M. Bronstein, Philippe Schwaller, Bruno E. Correia
2025 A* conf
Fully-inductive Node Classification on Arbitrary Graphs.
ICLR
Jianan Zhao, Zhaocheng Zhu, Mikhail Galkin, Hesham Mostafa, Michael M. Bronstein, Jian Tang
2025 J jnl
Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds.
CoRR
Oscar Davis, Michael S. Albergo, Nicholas M. Boffi, Michael M. Bronstein, Avishek Joey Bose
2025 J jnl
GradMetaNet: An Equivariant Architecture for Learning on Gradients.
CoRR
Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Michael M. Bronstein, Haggai Maron
2025 J jnl
Graph Kernel Neural Networks.
IEEE Trans. Neural Networks Learn. Syst.
Luca Cosmo, Giorgia Minello, Alessandro Bicciato, Michael M. Bronstein, Emanuele Rodolà, Luca Rossi, Andrea Torsello
2025 J jnl
GraphBench: Next-generation graph learning benchmarking.
CoRR
Timo Stoll, Chendi Qian, Ben Finkelshtein, Ali Parviz, Darius Weber, Fabrizio Frasca, Hadar Shavit, Antoine Siraudin, Arman Mielke, Marie Anastacio, Erik Müller, Maya Bechler-Speicher, Michael M. Bronstein, Mikhail Galkin, Holger H. Hoos, Mathias Niepert, Bryan Perozzi, Jan Tönshoff, Christopher Morris
2025 J jnl
HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs.
CoRR
Xingyue Huang, Mikhail Galkin, Michael M. Bronstein, Ismail Ilkan Ceylan
2025 A* conf
Homomorphism Counts as Structural Encodings for Graph Learning.
ICLR
Linus Bao, Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger
2025 A* conf
How Expressive are Knowledge Graph Foundation Models?
ICML
Xingyue Huang, Pablo Barceló, Michael M. Bronstein, Ismail Ilkan Ceylan, Mikhail Galkin, Juan L. Reutter, Miguel A. Romero Orth
2025 J jnl
How Expressive are Knowledge Graph Foundation Models?
CoRR
Xingyue Huang, Pablo Barceló, Michael M. Bronstein, Ismail Ilkan Ceylan, Mikhail Galkin, Juan L. Reutter, Miguel Romero
2025 J jnl
LLMs can hide text in other text of the same length.
CoRR
Antonio Norelli, Michael M. Bronstein
2025 J jnl
Learning Inter-Atomic Potentials without Explicit Equivariance.
CoRR
Ahmed A. A. Elhag, Arun Raja, Alex Morehead, Samuel M. Blau, Garrett M. Morris, Michael M. Bronstein
2025 J jnl
Link Prediction with Relational Hypergraphs.
Trans. Mach. Learn. Res.
Xingyue Huang, Miguel A. Romero Orth, Pablo Barceló, Michael M. Bronstein, Ismail Ilkan Ceylan
2025 J jnl
MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models.
CoRR
Kacper Kapusniak, Cristian Gabellini, Michael M. Bronstein, Prudencio Tossou, Francesco Di Giovanni
2025 J jnl
Mathematical Foundations of Geometric Deep Learning.
CoRR
Haitz Sáez de Ocáriz Borde, Michael M. Bronstein
2025 A* conf
Multi-domain Distribution Learning for De Novo Drug Design.
ICLR
Arne Schneuing, Ilia Igashov, Adrian W. Dobbelstein, Thomas Castiglione, Michael M. Bronstein, Bruno Correia
2025 J jnl
Multi-domain Distribution Learning for De Novo Drug Design.
CoRR
Arne Schneuing, Ilia Igashov, Adrian W. Dobbelstein, Thomas Castiglione, Michael M. Bronstein, Bruno E. Correia
2025 A* conf
Neural Spacetimes for DAG Representation Learning.
ICLR
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein
2025 J jnl
OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction.
CoRR
Emily Jin, Andrei Cristian Nica, Mikhail Galkin, Jarrid Rector-Brooks, Kin Long Kelvin Lee, Santiago Miret, Frances H. Arnold, Michael M. Bronstein, Avishek Joey Bose, Alexander Tong, Cheng-Hao Liu
2025 J jnl
Of Graphs and Tables: Zero-Shot Node Classification with Tabular Foundation Models.
CoRR
Adrian Hayler, Xingyue Huang, Ismail Ilkan Ceylan, Michael M. Bronstein, Ben Finkelshtein
2025 A* conf
On Measuring Long-Range Interactions in Graph Neural Networks.
ICML
Jacob Bamberger, Benjamin Gutteridge, Scott le Roux, Michael M. Bronstein, Xiaowen Dong
2025 J jnl
On Measuring Long-Range Interactions in Graph Neural Networks.
CoRR
Jacob Bamberger, Benjamin Gutteridge, Scott le Roux, Michael M. Bronstein, Xiaowen Dong
2025 J jnl
On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning.
CoRR
Alvaro Arroyo, Alessio Gravina, Benjamin Gutteridge, Federico Barbero, Claudio Gallicchio, Xiaowen Dong, Michael M. Bronstein, Pierre Vandergheynst
2025 — conf
On the Impact of Downstream Tasks on Sampling and Reconstructing Noisy Graph Signals.
CAMSAP
Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2025 J jnl
On the Impact of Downstream Tasks on Sampling and Reconstructing Noisy Graph Signals.
CoRR
Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2025 J jnl
Over-squashing in Spatiotemporal Graph Neural Networks.
CoRR
Ivan Marisca, Jacob Bamberger, Cesare Alippi, Michael M. Bronstein
2025 J jnl
Planner Aware Path Learning in Diffusion Language Models Training.
CoRR
Fred Zhangzhi Peng, Zachary Bezemek, Jarrid Rector-Brooks, Shuibai Zhang, Anru R. Zhang, Michael M. Bronstein, Avishek Joey Bose, Alexander Tong
2025 — conf
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.
ICML (Position Papers)
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2025 J jnl
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.
CoRR
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2025 J jnl
Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities.
CoRR
Tara Akhound-Sadegh, Jungyoon Lee, Avishek Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong
2025 J jnl
ResCP: Reservoir Conformal Prediction for Time Series Forecasting.
CoRR
Roberto Neglia, Andrea Cini, Michael M. Bronstein, Filippo Maria Bianchi
2025 A* conf
Scalable Equilibrium Sampling with Sequential Boltzmann Generators.
ICML
Charlie B. Tan, Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong
2025 J jnl
Scalable Equilibrium Sampling with Sequential Boltzmann Generators.
CoRR
Charlie B. Tan, Avishek Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong
2025 J jnl
Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning.
CoRR
Zifeng Ding, Shenyang Huang, Zeyu Cao, Emma Kondrup, Zachary Yang, Xingyue Huang, Yuan Sui, Zhangdie Yuan, Yuqicheng Zhu, Xianglong Hu, Yuan He, Farimah Poursafaei, Michael M. Bronstein, Andreas Vlachos
2025 J jnl
Setting the Record Straight on Transformer Oversmoothing.
Trans. Mach. Learn. Res.
Gbètondji J.-S. Dovonon, Michael M. Bronstein, Matt J. Kusner
2025 A* conf
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction.
ICLR
Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose
2025 A* conf
Supercharging Graph Transformers with Advective Diffusion.
ICML
Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Michael M. Bronstein
2025 J jnl
TGM: a Modular and Efficient Library for Machine Learning on Temporal Graphs.
CoRR
Jacob Chmura, Shenyang Huang, Tran Gia Bao Ngo, Ali Parviz, Farimah Poursafaei, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Matthias Fey, Reihaneh Rabbany
2025 — conf
Temporal Graph Learning Workshop.
KDD (2)
Shenyang Huang, Daniele Zambon, Andrea Cini, Farimah Poursafaei, Jacob Chmura, Julia Gastinger, Reihaneh Rabbany, Michael M. Bronstein
2025 A* conf
Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.
ICLR
Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron
2025 J jnl
Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement.
CoRR
Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, Michael M. Bronstein, Xiaowen Dong
2025 A* conf
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity.
ICLR
Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer
2025 J jnl
Why do LLMs attend to the first token?
CoRR
Federico Barbero, Alvaro Arroyo, Xiangming Gu, Christos Perivolaropoulos, Michael M. Bronstein, Petar Velickovic, Razvan Pascanu
2025 J jnl
gLSTM: Mitigating Over-Squashing by Increasing Storage Capacity.
CoRR
Hugh Blayney, Alvaro Arroyo, Xiaowen Dong, Michael M. Bronstein
2024 J jnl
Advancing Graph Convolutional Networks via General Spectral Wavelets.
CoRR
Nian Liu, Xiaoxin He, Thomas Laurent, Francesco Di Giovanni, Michael M. Bronstein, Xavier Bresson
2024 J jnl
Bundle Neural Networks for message diffusion on graphs.
CoRR
Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein
2024 A* conf
Cooperative Graph Neural Networks.
ICML
Ben Finkelshtein, Xingyue Huang, Michael M. Bronstein, Ismail Ilkan Ceylan
2024 J jnl
DyGMamba: Efficiently Modeling Long-Term Temporal Dependency on Continuous-Time Dynamic Graphs with State Space Models.
CoRR
Zifeng Ding, Yifeng Li, Yuan He, Antonio Norelli, Jingcheng Wu, Volker Tresp, Yunpu Ma, Michael M. Bronstein
2024 J jnl
Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification.
CoRR
Benedict Aaron Tjandra, Federico Barbero, Michael M. Bronstein
2024 J jnl
Equivariant 3D-conditional diffusion model for molecular linker design.
Nat. Mac. Intell.
Ilia Igashov, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia
2024 A* conf
Fisher Flow Matching for Generative Modeling over Discrete Data.
NeurIPS
Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ilkan Ceylan, Michael M. Bronstein, Avishek Joey Bose
2024 J jnl
Fisher Flow Matching for Generative Modeling over Discrete Data.
CoRR
Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ilkan Ceylan, Michael M. Bronstein, Avishek Joey Bose
2024 A* conf
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module.
ICLR
Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo
2024 J jnl
Future Directions in Foundations of Graph Machine Learning.
CoRR
Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024 J jnl
Generative Active Learning for the Search of Small-molecule Protein Binders.
CoRR
Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio
2024 J jnl
GraphAny: A Foundation Model for Node Classification on Any Graph.
CoRR
Jianan Zhao, Hesham Mostafa, Mikhail Galkin, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang
2024 J jnl
Homomorphism Counts as Structural Encodings for Graph Learning.
CoRR
Linus Bao, Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger
2024 A* conf
Homomorphism Counts for Graph Neural Networks: All About That Basis.
ICML
Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger
2024 J jnl
Homomorphism Counts for Graph Neural Networks: All About That Basis.
CoRR
Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger
2024 J jnl
How does over-squashing affect the power of GNNs?
Trans. Mach. Learn. Res.
Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic
2024 A* conf
Learning on Large Graphs using Intersecting Communities.
NeurIPS
Ben Finkelshtein, Ismail Ilkan Ceylan, Michael M. Bronstein, Ron Levie
2024 J jnl
Learning on Large Graphs using Intersecting Communities.
CoRR
Ben Finkelshtein, Ismail Ilkan Ceylan, Michael M. Bronstein, Ron Levie
2024 J jnl
Link Prediction with Relational Hypergraphs.
CoRR
Xingyue Huang, Miguel A. Romero Orth, Pablo Barceló, Michael M. Bronstein, Ismail Ilkan Ceylan
2024 A* conf
Locality-Aware Graph Rewiring in GNNs.
ICLR
Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni
2024 J jnl
Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural Networks.
CoRR
T. Konstantin Rusch, Nathan Kirk, Michael M. Bronstein, Christiane Lemieux, Daniela Rus
2024 A* conf
Metric Flow Matching for Smooth Interpolations on the Data Manifold.
NeurIPS
Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni
2024 J jnl
Metric Flow Matching for Smooth Interpolations on the Data Manifold.
CoRR
Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni
2024 J jnl
Neural Spacetimes for DAG Representation Learning.
CoRR
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein
2024 J jnl
On the Impact of Sample Size in Reconstructing Noisy Graph Signals: A Theoretical Characterisation.
CoRR
Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2024 A* conf
On the Limitations of Fractal Dimension as a Measure of Generalization.
NeurIPS
Charlie Tan, Inés García-Redondo, Qiquan Wang, Michael M. Bronstein, Anthea Monod
2024 J jnl
On the Limitations of Fractal Dimension as a Measure of Generalization.
CoRR
Charlie Tan, Inés García-Redondo, Qiquan Wang, Michael M. Bronstein, Anthea Monod
2024 J jnl
OpenQDC: Open Quantum Data Commons.
CoRR
Cristian Gabellini, Nikhil Shenoy, Stephan Thaler, Semih Cantürk, Daniel McNeela, Dominique Beaini, Michael M. Bronstein, Prudencio Tossou
2024 J jnl
Position Paper: Challenges and Opportunities in Topological Deep Learning.
CoRR
Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
2024 A* conf
Position: Future Directions in the Theory of Graph Machine Learning.
ICML
Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024 A* conf
Position: Topological Deep Learning is the New Frontier for Relational Learning.
ICML
Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
2024 J jnl
Relaxed Equivariance via Multitask Learning.
CoRR
Ahmed A. A. Elhag, T. Konstantin Rusch, Francesco Di Giovanni, Michael M. Bronstein
2024 A* conf
RetroBridge: Modeling Retrosynthesis with Markov Bridges.
ICLR
Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia
2024 J jnl
Revealing Decurve Flows for Generalized Graph Propagation.
CoRR
Chen Lin, Liheng Ma, Yiyang Chen, Wanli Ouyang, Michael M. Bronstein, Philip H. S. Torr
2024 A* conf
SE(3)-Stochastic Flow Matching for Protein Backbone Generation.
ICLR
Avishek Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong
2024 J jnl
Scalable Message Passing Neural Networks: No Need for Attention in Large Graph Representation Learning.
CoRR
Haitz Sáez de Ocáriz Borde, Artem Lukoianov, Anastasis Kratsios, Michael M. Bronstein, Xiaowen Dong
2024 J jnl
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation.
CoRR
Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose
2024 A* conf
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation.
NeurIPS
Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose
2024 J jnl
Setting the Record Straight on Transformer Oversmoothing.
CoRR
Gbètondji J.-S. Dovonon, Michael M. Bronstein, Matt J. Kusner
2024 J jnl
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction.
CoRR
Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Yoshua Bengio, Pranam Chatterjee, Alexander Tong, Avishek Joey Bose
2024 J jnl
Structure-based drug design with equivariant diffusion models.
Nat. Comput. Sci.
Arne Schneuing, Charles Harris, Yuanqi Du, Kieran Didi, Arian Rokkum Jamasb, Ilia Igashov, Weitao Du, Carla P. Gomes, Tom L. Blundell, Pietro Lio, Max Welling, Michael M. Bronstein, Bruno E. Correia
2024 — conf
The 1st International Workshop on Graph Foundation Models (GFM).
WWW (Companion Volume)
Haitao Mao, Jianan Zhao, Xiaoxin He, Zhikai Chen, Qian Huang, Zhaocheng Zhu, Jian Tang, Michael M. Bronstein, Xavier Bresson, Bryan Hooi, Haiyang Zhang, Xianfeng Tang, Luo Chen, Jiliang Tang
2024 A conf
To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion models.
UAI
Teodora Reu, Francisco Vargas, Anna Kerekes, Michael M. Bronstein
2024 J jnl
Topological Blind Spots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.
CoRR
Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron
2024 J jnl
Understanding Virtual Nodes: Oversmoothing, Oversquashing, and Node Heterogeneity.
CoRR
Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer
2023 J jnl
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems.
CoRR
Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein
2023 J jnl
A Survey on Oversmoothing in Graph Neural Networks.
CoRR
T. Konstantin Rusch, Michael M. Bronstein, Siddhartha Mishra
2023 J jnl
Advective Diffusion Transformers for Topological Generalization in Graph Learning.
CoRR
Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Fan Nie, Michael M. Bronstein, Junchi Yan
2023 J jnl
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
CoRR
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2023 — conf
Can strong structural encoding reduce the importance of Message Passing?
TAG-ML
Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni
2023 J jnl
Can strong structural encoding reduce the importance of Message Passing?
CoRR
Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni
2023 J jnl
Cooperative Graph Neural Networks.
CoRR
Ben Finkelshtein, Xingyue Huang, Michael M. Bronstein, Ismail Ilkan Ceylan
2023 A* conf
Curvature Filtrations for Graph Generative Model Evaluation.
NeurIPS
Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck
2023 J jnl
Curvature Filtrations for Graph Generative Model Evaluation.
CoRR
Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck
2023 A* conf
DRew: Dynamically Rewired Message Passing with Delay.
ICML
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
2023 J jnl
DRew: Dynamically Rewired Message Passing with Delay.
CoRR
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
2023 J jnl
Differentiable Graph Module (DGM) for Graph Convolutional Networks.
IEEE Trans. Pattern Anal. Mach. Intell.
Anees Kazi, Luca Cosmo, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein
2023 — conf
Edge Directionality Improves Learning on Heterophilic Graphs.
LoG
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
2023 J jnl
Edge Directionality Improves Learning on Heterophilic Graphs.
CoRR
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
2023 J jnl
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module.
CoRR
Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo
2023 A* conf
Gradient Gating for Deep Multi-Rate Learning on Graphs.
ICLR
T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra
2023 A* conf
Graph Neural Networks for Link Prediction with Subgraph Sketching.
ICLR
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire
2023 J jnl
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications.
Medical Image Anal.
Kamilia Zaripova, Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Michael M. Bronstein, Nassir Navab
2023 J jnl
GraphText: Graph Reasoning in Text Space.
CoRR
Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang
2023 J jnl
How does over-squashing affect the power of GNNs?
CoRR
Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic
2023 A* conf
Hyperbolic Deep Reinforcement Learning.
ICLR
Edoardo Cetin, Benjamin Paul Chamberlain, Michael M. Bronstein, Jonathan J. Hunt
2023 J jnl
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
IEEE Trans. Pattern Anal. Mach. Intell.
Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein
2023 J jnl
Locality-Aware Graph-Rewiring in GNNs.
CoRR
Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni
2023 A* conf
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology.
ICML
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein
2023 J jnl
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology.
CoRR
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio', Michael M. Bronstein
2023 J jnl
On the Impact of Sample Size in Reconstructing Graph Signals.
CoRR
Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2023 A* conf
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization.
AAAI
Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli
2023 J jnl
RetroBridge: Modeling Retrosynthesis with Markov Bridges.
CoRR
Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia
2023 J jnl
SE(3)-Stochastic Flow Matching for Protein Backbone Generation.
CoRR
Avishek Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong
2023 J jnl
Social learning across symbolic cultural barriers in non-human cultures.
CoRR
António Leitão, Maxime Lucas, Simone Poetto, Taylor A. Hersh, Shane Gero, David F. Gruber, Michael M. Bronstein, Giovanni Petri
2023 A* conf
Temporal Graph Benchmark for Machine Learning on Temporal Graphs.
NeurIPS
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
2023 J jnl
Temporal Graph Benchmark for Machine Learning on Temporal Graphs.
CoRR
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
2023 J jnl
Understanding convolution on graphs via energies.
Trans. Mach. Learn. Res.
Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein
2022 J jnl
3D Shape Analysis Through a Quantum Lens: the Average Mixing Kernel Signature.
Int. J. Comput. Vis.
Luca Cosmo, Giorgia Minello, Michael M. Bronstein, Emanuele Rodolà, Luca Rossi, Andrea Torsello
2022 J jnl
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design.
CoRR
Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia
2022 A* conf
Equivariant Subgraph Aggregation Networks.
ICLR
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2022 J jnl
Gradient Gating for Deep Multi-Rate Learning on Graphs.
CoRR
T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra
2022 J jnl
Graph Anisotropic Diffusion.
CoRR
Ahmed A. A. Elhag, Gabriele Corso, Hannes Stärk, Michael M. Bronstein
2022 J jnl
Graph Neural Networks as Gradient Flows.
CoRR
Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein
2022 J jnl
Graph Neural Networks for Link Prediction with Subgraph Sketching.
CoRR
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Hammerla, Michael M. Bronstein, Max Hansmire
2022 A* conf
Graph-Coupled Oscillator Networks.
ICML
T. Konstantin Rusch, Ben Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein
2022 J jnl
Graph-Coupled Oscillator Networks.
CoRR
T. Konstantin Rusch, Benjamin Paul Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein
2022 A* conf
Graph-based Representation Learning for Web-scale Recommender Systems.
KDD
Ahmed El-Kishky, Michael M. Bronstein, Ying Xiao, Aria Haghighi
2022 J jnl
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications.
CoRR
Kamilia Mullakaeva, Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein
2022 J jnl
Guest Editorial: Non-Euclidean Machine Learning.
IEEE Trans. Pattern Anal. Mach. Intell.
Stefanos Zafeiriou, Michael M. Bronstein, Taco Cohen, Oriol Vinyals, Le Song, Jure Leskovec, Pietro Liò, Joan Bruna, Marco Gori
2022 J jnl
Heterogeneous manifolds for curvature-aware graph embedding.
CoRR
Francesco Di Giovanni, Giulia Luise, Michael M. Bronstein
2022 J jnl
Hyperbolic Deep Reinforcement Learning.
CoRR
Edoardo Cetin, Benjamin Paul Chamberlain, Michael M. Bronstein, Jonathan J. Hunt
2022 — ed.
Imaging Systems for GI Endoscopy, and Graphs in Biomedical Image Analysis - First MICCAI Workshop, ISGIE 2022, and Fourth MICCAI Workshop, GRAIL 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
ISGIE/GRAIL@MICCAI
Luigi Manfredi, Seyed-Ahmad Ahmadi, Michael M. Bronstein, Anees Kazi, Davide Lomanto, Alwyn Mathew, Ludovic Magerand, Kamilia Mullakaeva, Bartlomiej W. Papiez, Russell H. Taylor, Emanuele Trucco
2022 — conf
Inverse Computational Spectral Geometry.
Eurographics (Tutorials)
Emanuele Rodolà, Luca Cosmo, Maks Ovsjanikov, Arianna Rampini, Simone Melzi, Michael M. Bronstein, Riccardo Marin
2022 A* conf
Learning to Infer Structures of Network Games.
ICML
Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong
2022 J jnl
Learning to Infer Structures of Network Games.
CoRR
Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong
2022 J jnl
Matching 3D Facial Shape to Demographic Properties by Geometric Metric Learning: A Part-Based Approach.
IEEE Trans. Biom. Behav. Identity Sci.
Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris, Giorgos Bouritsas, Shunwang Gong, Susan Walsh, Mark D. Shriver, Michael M. Bronstein, Peter Claes
2022 J jnl
Multi-Scale Part-Based Syndrome Classification of 3D Facial Images.
IEEE Access
Soha Sadat Mahdi, Harold S. Matthews, Nele Nauwelaers, Michiel Vanneste, Shunwang Gong, Giorgos Bouritsas, Gareth S. Baynam, Peter Hammond, Richard A. Spritz, Ophir D. Klein, Benedikt Hallgrímsson, Hilde Peeters, Michael M. Bronstein, Peter Claes
2022 — conf
Neural Diffusion PDEs, Differential Geometry, and Graph Neural Networks.
IMPROVE
Michael M. Bronstein
2022 A* conf
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs.
NeurIPS
Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein
2022 J jnl
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs.
CoRR
Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Liò, Michael M. Bronstein
2022 — conf
On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs With Missing Node Features.
LoG
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2022 J jnl
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization.
CoRR
Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli
2022 J jnl
RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro.
CoRR
Paul Bertin, Jarrid Rector-Brooks, Deepak Sharma, Thomas Gaudelet, Andrew Anighoro, Torsten Gross, Francisco Martinez-Pena, Eileen L. Tang, Suraj M. S, Cristian Regep, Jeremy B. R. Hayter, Maksym Korablyov, Nicholas Valiante, Almer van der Sloot, Mike Tyers, Charles Roberts, Michael M. Bronstein, Luke L. Lairson, Jake P. Taylor-King, Yoshua Bengio
2022 — conf
Sheaf Neural Networks with Connection Laplacians.
TAG-ML
Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò
2022 J jnl
Sheaf Neural Networks with Connection Laplacians.
CoRR
Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò
2022 J jnl
Structure-based Drug Design with Equivariant Diffusion Models.
CoRR
Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia
2022 A* conf
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.
NeurIPS
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
2022 J jnl
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.
CoRR
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
2022 A* conf
Understanding over-squashing and bottlenecks on graphs via curvature.
ICLR
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2021 A* conf
Beltrami Flow and Neural Diffusion on Graphs.
NeurIPS
Ben Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
2021 J jnl
Beltrami Flow and Neural Diffusion on Graphs.
CoRR
Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
2021 J jnl
Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales.
CoRR
Jacob Andreas, Gasper Begus, 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 M. Vogt, Robert J. Wood
2021 J jnl
Equivariant Subgraph Aggregation Networks.
CoRR
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2021 A* conf
Fast End-to-End Learning on Protein Surfaces.
CVPR
Freyr Sverrisson, Jean Feydy, Bruno E. Correia, Michael M. Bronstein
2021 A* conf
GRAND: Graph Neural Diffusion.
ICML
Ben Chamberlain, James Rowbottom, Maria I. Gorinova, Michael M. Bronstein, Stefan Webb, Emanuele Rossi
2021 J jnl
GRAND: Graph Neural Diffusion.
CoRR
Benjamin Paul Chamberlain, James Rowbottom, Maria I. Gorinova, Stefan Webb, Emanuele Rossi, Michael M. Bronstein
2021 A conf
GReS: Workshop on Graph Neural Networks for Recommendation and Search.
RecSys
Thibaut Thonet, Stéphane Clinchant, Carlos Lassance, Elvin Isufi, Jiaqi Ma, Yutong Xie, Jean-Michel Renders, Michael M. Bronstein
2021 J jnl
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.
CoRR
Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Velickovic
2021 J jnl
Graph Kernel Neural Networks.
CoRR
Luca Cosmo, Giorgia Minello, Michael M. Bronstein, Emanuele Rodolà, Luca Rossi, Andrea Torsello
2021 J jnl
Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit.
J. Sci. Comput.
Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai
2021 J jnl
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features.
CoRR
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2021 J jnl
Orthogonalized Fourier Polynomials for Signal Approximation and Transfer.
Comput. Graph. Forum
Filippo Maggioli, Simone Melzi, Maksim Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà
2021 A* conf
Partition and Code: learning how to compress graphs.
NeurIPS
Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein
2021 J jnl
Partition and Code: learning how to compress graphs.
CoRR
Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein
2021 A conf
RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter's Home Timeline.
RecSys
Vito Walter Anelli, Saikishore Kalloori, Bruce Ferwerda, Luca Belli, Alykhan Tejani, Frank Portman, Alexandre Lung-Yut-Fong, Ben Chamberlain, Yuanpu Xie, Jonathan Hunt, Michael M. Bronstein, Wenzhe Shi
2021 J jnl
Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation.
Int. J. Comput. Vis.
Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou
2021 — conf
The 2021 RecSys Challenge Dataset: Fairness is not optional.
RecSys Challenge
Luca Belli, Alykhan Tejani, Frank Portman, Alexandre Lung-Yut-Fong, Ben Chamberlain, Yuanpu Xie, Kristian Lum, Jonathan Hunt, Michael M. Bronstein, Vito Walter Anelli, Saikishore Kalloori, Bruce Ferwerda, Wenzhe Shi
2021 J jnl
The 2021 RecSys Challenge Dataset: Fairness is not optional.
CoRR
Luca Belli, Alykhan Tejani, Frank Portman, Alexandre Lung-Yut-Fong, Ben Chamberlain, Yuanpu Xie, Kristian Lum, Jonathan Hunt, Michael M. Bronstein, Vito Walter Anelli, Saikishore Kalloori, Bruce Ferwerda, Wenzhe Shi
2021 J jnl
Transferability of Spectral Graph Convolutional Neural Networks.
J. Mach. Learn. Res.
Ron Levie, Wei Huang, Lorenzo Bucci, Michael M. Bronstein, Gitta Kutyniok
2021 J jnl
Understanding over-squashing and bottlenecks on graphs via curvature.
CoRR
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2021 J jnl
Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling.
CoRR
Balder Croquet, Daan Christiaens, Seth M. Weinberg, Michael M. Bronstein, Dirk Vandermeulen, Peter Claes
2021 — conf
Unsupervised Diffeomorphic Surface Registration and Non-linear Modelling.
MICCAI (4)
Balder Croquet, Daan Christiaens, Seth M. Weinberg, Michael M. Bronstein, Dirk Vandermeulen, Peter Claes
2021 J jnl
Utilizing graph machine learning within drug discovery and development.
Briefings Bioinform.
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
2021 A* conf
Weisfeiler and Lehman Go Cellular: CW Networks.
NeurIPS
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein
2021 J jnl
Weisfeiler and Lehman Go Cellular: CW Networks.
CoRR
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael M. Bronstein
2021 A* conf
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.
ICML
Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein
2021 J jnl
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.
CoRR
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael M. Bronstein
2020 B conf
3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties.
ICPR
Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris, Giorgos Bouritsas, Shunwang Gong, Sergiy Bokhnyak, Susan Walsh, Mark D. Shriver, Michael M. Bronstein, Peter Claes
2020 J jnl
3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties.
CoRR
Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris, Giorgos Bouritsas, Shunwang Gong, Sergiy Bokhnyak, Susan Walsh, Mark D. Shriver, Michael M. Bronstein, Peter Claes
2020 B conf
Clustered Dynamic Graph CNN for Biometric 3D Hand Shape Recognition.
IJCB
Jan Svoboda, Pietro Astolfi, Davide Boscaini, Jonathan Masci, Michael M. Bronstein
2020 J jnl
Differentiable Graph Module (DGM) Graph Convolutional Networks.
CoRR
Anees Kazi, Luca Cosmo, Nassir Navab, Michael M. Bronstein
2020 A* conf
Fast geometric learning with symbolic matrices.
NeurIPS
Jean Feydy, Joan Alexis Glaunès, Benjamin Charlier, Michael M. Bronstein
2020 A* conf
Geometrically Principled Connections in Graph Neural Networks.
CVPR
Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou
2020 J jnl
Geometrically Principled Connections in Graph Neural Networks.
CoRR
Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou
2020 J jnl
Graph Attentional Autoencoder for Anticancer Hyperfood Prediction.
CoRR
Guadalupe Gonzalez, Shunwang Gong, Ivan Laponogov, Kirill A. Veselkov, Michael M. Bronstein
2020 J jnl
Graph Signal Processing for Machine Learning: A Review and New Perspectives.
IEEE Signal Process. Mag.
Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard
2020 J jnl
Graph signal processing for machine learning: A review and new perspectives.
CoRR
Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard
2020 J jnl
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
CoRR
Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein
2020 J jnl
Intel® RealSense™ SR300 Coded Light Depth Camera.
IEEE Trans. Pattern Anal. Mach. Intell.
Aviad Zabatani, Vitaly Surazhsky, Erez Sperling, Sagi Ben-Moshe, Ohad Menashe, David H. Silver, Zachi Karni, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2020 J jnl
Latent Patient Network Learning for Automatic Diagnosis.
CoRR
Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein
2020 — conf
Latent-Graph Learning for Disease Prediction.
MICCAI (2)
Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein
2020 J jnl
Non-Rigid Puzzles.
CoRR
Or Litany, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronstein, Daniel Cremers
2020 J jnl
Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline.
CoRR
Luca Belli, Sofia Ira Ktena, Alykhan Tejani, Alexandre Lung-Yut-Fong, Frank Portman, Xiao Zhu, Yuanpu Xie, Akshay Gupta, Michael M. Bronstein, Amra Delic, Gabriele Sottocornola, Vito Walter Anelli, Nazareno Andrade, Jessie Smith, Wenzhe Shi
2020 A conf
RecSys 2020 Challenge Workshop: Engagement Prediction on Twitter's Home Timeline.
RecSys
Vito Walter Anelli, Amra Delic, Gabriele Sottocornola, Jessie Smith, Nazareno Andrade, Luca Belli, Michael M. Bronstein, Akshay Gupta, Sofia Ira Ktena, Alexandre Lung-Yut-Fong, Frank Portman, Alykhan Tejani, Yuanpu Xie, Xiao Zhu, Wenzhe Shi
2020 J jnl
SIGN: Scalable Inception Graph Neural Networks.
CoRR
Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti
2020 J jnl
Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation.
CoRR
Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou
2020 J jnl
Shape retrieval of non-rigid 3d human models.
CoRR
David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, Long Lai, Bo Li, Chunyuan Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Li Sun, Gary K. L. Tam, Atsushi Tatsuma, Jianbo Ye
2020 J jnl
Temporal Graph Networks for Deep Learning on Dynamic Graphs.
CoRR
Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, Michael M. Bronstein
2020 — conf
The Average Mixing Kernel Signature.
ECCV (20)
Luca Cosmo, Giorgia Minello, Michael M. Bronstein, Luca Rossi, Andrea Torsello
2020 A conf
Tuning Word2vec for Large Scale Recommendation Systems.
RecSys
Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein
2020 J jnl
Tuning Word2vec for Large Scale Recommendation Systems.
CoRR
Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein
2020 J jnl
Utilising Graph Machine Learning within Drug Discovery and Development.
CoRR
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
2020 A* conf
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild.
CVPR
Dominik Kulon, Riza Alp Güler, Iasonas Kokkinos, Michael M. Bronstein, Stefanos Zafeiriou
2020 J jnl
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild.
CoRR
Dominik Kulon, Riza Alp Güler, Iasonas Kokkinos, Michael M. Bronstein, Stefanos Zafeiriou
2019 J jnl
CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters.
IEEE Trans. Signal Process.
Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein
2019 — conf
Deep Learning for Computer Graphics and Geometry Processing.
Eurographics (Tutorials)
Michael M. Bronstein, Leonidas J. Guibas, Iasonas Kokkinos, Or Litany, Niloy J. Mitra, Federico Monti, Emanuele Rodolà
2019 J jnl
Dynamic Graph CNN for Learning on Point Clouds.
ACM Trans. Graph.
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon
2019 J jnl
Fake News Detection on Social Media using Geometric Deep Learning.
CoRR
Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein
2019 J jnl
Functional Maps Representation On Product Manifolds.
Comput. Graph. Forum
Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon
2019 A* conf
GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching.
CVPR
Simone Melzi, Riccardo Spezialetti, Federico Tombari, Michael M. Bronstein, Luigi Di Stefano, Emanuele Rodolà
2019 A* conf
Isospectralization, or How to Hear Shape, Style, and Correspondence.
CVPR
Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà
2019 J jnl
Learning interpretable disease self-representations for drug repositioning.
CoRR
Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill A. Veselkov, Alberto Paccanaro, Michael M. Bronstein
2019 J jnl
MeshGAN: Non-linear 3D Morphable Models of Faces.
CoRR
Shiyang Cheng, Michael M. Bronstein, Yuxiang Zhou, Irene Kotsia, Maja Pantic, Stefanos Zafeiriou
2019 A* conf
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation.
ICCV
Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Stefanos Zafeiriou, Michael M. Bronstein
2019 J jnl
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation.
CoRR
Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Michael M. Bronstein, Stefanos Zafeiriou
2019 — conf
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks.
ICLR (Poster)
Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas
2019 — conf
Shape Correspondence with Isometric and Non-Isometric Deformations.
3DOR@Eurographics
Roberto M. Dyke, C. Stride, Yu-Kun Lai, Paul L. Rosin, Mathieu Aubry, Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers, Matthew Fisher, Thibault Groueix, Daoliang Guo, Vladimir G. Kim, Ron Kimmel, Zorah Lähner, Kun Li, Or Litany, Tal Remez, Emanuele Rodolà, Bryan C. Russell, Yusuf Sahillioglu, Ron Slossberg, Gary K. L. Tam, Matthias Vestner, Z. Wu, Jingyu Yang
2019 A conf
Single Image 3D Hand Reconstruction with Mesh Convolutions.
BMVC
Dominik Kulon, Haoyang Wang, Riza Alp Güler, Michael M. Bronstein, Stefanos Zafeiriou
2019 J jnl
Single Image 3D Hand Reconstruction with Mesh Convolutions.
CoRR
Dominik Kulon, Haoyang Wang, Riza Alp Güler, Michael M. Bronstein, Stefanos Zafeiriou
2019 — conf
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator.
ICCV Workshops
Shunwang Gong, Lei Chen, Michael M. Bronstein, Stefanos Zafeiriou
2019 J jnl
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator.
CoRR
Shunwang Gong, Lei Chen, Michael M. Bronstein, Stefanos Zafeiriou
2019 J jnl
Transferability of Spectral Graph Convolutional Neural Networks.
CoRR
Ron Levie, Michael M. Bronstein, Gitta Kutyniok
2019 J jnl
ncRNA Classification with Graph Convolutional Networks.
CoRR
Emanuele Rossi, Federico Monti, Michael M. Bronstein, Pietro Liò
2018 Misc conf
Deep Geometric Matrix Completion: A New Way for Recommender Systems.
ICASSP
Federico Monti, Michael M. Bronstein, Xavier Bresson
2018 A* conf
Deformable Shape Completion With Graph Convolutional Autoencoders.
CVPR
Or Litany, Alexander M. Bronstein, Michael M. Bronstein, Ameesh Makadia
2018 J jnl
Dual-Primal Graph Convolutional Networks.
CoRR
Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein
2018 J jnl
Dynamic Graph CNN for Learning on Point Clouds.
CoRR
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon
2018 J jnl
Functional Maps Representation on Product Manifolds.
CoRR
Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon
2018 — conf
Functional Maps on Product Manifolds.
SGP (Posters)
Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein, Michael M. Bronstein, Justin Solomon
2018 C conf
Graph Neural Networks for IceCube Signal Classification.
ICMLA
Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna
2018 J jnl
Graph Neural Networks for IceCube Signal Classification.
CoRR
Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna
2018 J jnl
Improved Functional Mappings via Product Preservation.
Comput. Graph. Forum
Dorian Nogneng, Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein, Maks Ovsjanikov
2018 J jnl
Interactive Curve Constrained Functional Maps.
Comput. Graph. Forum
Anne Gehre, Michael M. Bronstein, Leif Kobbelt, Justin Solomon
2018 J jnl
Isospectralization, or how to hear shape, style, and correspondence.
CoRR
Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà
2018 J jnl
Kernel Functional Maps.
Comput. Graph. Forum
Larry Wang, Anne Gehre, Michael M. Bronstein, Justin Solomon
2018 J jnl
Localized Manifold Harmonics for Spectral Shape Analysis.
Comput. Graph. Forum
Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein
2018 — conf
MOTIFNET: A Motif-Based Graph Convolutional Network for Directed Graphs.
DSW
Federico Monti, Karl Otness, Michael M. Bronstein
2018 J jnl
MotifNet: a motif-based Graph Convolutional Network for directed graphs.
CoRR
Federico Monti, Karl Otness, Michael M. Bronstein
2018 J jnl
Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit.
CoRR
Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai
2018 J jnl
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks.
CoRR
Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas
2017 J jnl
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters.
CoRR
Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein
2017 — conf
Computing and processing correspondences with functional maps.
SIGGRAPH Courses
Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein
2017 A* conf
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence.
ICCV
Or Litany, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein
2017 J jnl
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence.
CoRR
Or Litany, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein
2017 J jnl
Deformable Shape Completion with Graph Convolutional Autoencoders.
CoRR
Or Litany, Alexander M. Bronstein, Michael M. Bronstein, Ameesh Makadia
2017 — conf
Deformable Shape Retrieval with Missing Parts.
3DOR@Eurographics
Emanuele Rodolà, Luca Cosmo, Or Litany, Michael M. Bronstein, Alexander M. Bronstein, Nicolas Audebert, A. Ben Hamza, Alexandre Boulch, Umberto Castellani, Minh N. Do, Duc Anh Duong, Takahiko Furuya, Andrea Gasparetto, Y. Hong, J. Kim, Bertrand Le Saux, Roee Litman, Majid Masoumi, Giorgia Minello, Hai-Dang Nguyen, V.-T. Nguyen, Ryutarou Ohbuchi, Viet-Khoi Pham, Thuyen V. Phan, M. Rezaei, Andrea Torsello, Minh-Triet Tran, Q. T. Tran, Bao Truong, L. Wan, Changqing Zou
2017 — conf
Efficient Deformable Shape Correspondence via Kernel Matching.
3DV
Matthias Vestner, Zorah Lähner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers
2017 J jnl
Efficient Deformable Shape Correspondence via Kernel Matching.
CoRR
Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers
2017 J jnl
Fully Spectral Partial Shape Matching.
Comput. Graph. Forum
Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein
2017 J jnl
Generative Convolutional Networks for Latent Fingerprint Reconstruction.
CoRR
Jan Svoboda, Federico Monti, Michael M. Bronstein
2017 B conf
Generative convolutional networks for latent fingerprint reconstruction.
IJCB
Jan Svoboda, Federico Monti, Michael M. Bronstein
2017 A* conf
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs.
CVPR
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein
2017 J jnl
Geometric Deep Learning: Going beyond Euclidean data.
IEEE Signal Process. Mag.
Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst
2017 — conf
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks.
NIPS
Federico Monti, Michael M. Bronstein, Xavier Bresson
2017 J jnl
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks.
CoRR
Federico Monti, Michael M. Bronstein, Xavier Bresson
2017 — conf
Localized Manifold Harmonics for Spectral Shape Analysis.
SGP (Posters)
Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein
2017 J jnl
Localized Manifold Harmonics for Spectral Shape Analysis.
CoRR
Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein
2017 J jnl
Partial Functional Correspondence.
Comput. Graph. Forum
Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers
2017 — conf
Spatial Maps: From Low Rank Spectral to Sparse Spatial Functional Representations.
3DV
Andrea Gasparetto, Luca Cosmo, Emanuele Rodolà, Michael M. Bronstein, Andrea Torsello
2017 — conf
Subspace Least Squares Multidimensional Scaling.
SSVM
Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein
2017 J jnl
Subspace Least Squares Multidimensional Scaling.
CoRR
Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein
2016 J jnl
Anisotropic Diffusion Descriptors.
Comput. Graph. Forum
Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers
2016 — conf
Computing and processing correspondences with functional maps.
SIGGRAPH ASIA Courses
Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein
2016 — conf
Coupled Functional Maps.
3DV
Davide Eynard, Emanuele Rodolà, Klaus Glashoff, Michael M. Bronstein
2016 — conf
Deep Learning for Shape Analysis.
Eurographics (Tutorials)
Michael M. Bronstein, Evangelos Kalogerakis, Emanuele Rodolà, Jonathan Masci, Davide Boscaini
2016 A* conf
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching.
CVPR
Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers
2016 J jnl
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching.
CoRR
Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers
2016 J jnl
Geometric deep learning on graphs and manifolds using mixture model CNNs.
CoRR
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein
2016 — conf
Geometric deep learning.
SIGGRAPH ASIA Courses
Jonathan Masci, Emanuele Rodolà, Davide Boscaini, Michael M. Bronstein, Hao Li
2016 J jnl
Geometric deep learning: going beyond Euclidean data.
CoRR
Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst
2016 — conf
Learning shape correspondence with anisotropic convolutional neural networks.
NIPS
Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein
2016 J jnl
Learning shape correspondence with anisotropic convolutional neural networks.
CoRR
Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein
2016 — conf
MADMM: A Generic Algorithm for Non-smooth Optimization on Manifolds.
ECCV (5)
Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein
2016 — conf
Matching Deformable Objects in Clutter.
3DV
Luca Cosmo, Emanuele Rodolà, Jonathan Masci, Andrea Torsello, Michael M. Bronstein
2016 — conf
Matching of Deformable Shapes with Topological Noise.
3DOR@Eurographics
Zorah Lähner, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers, Oliver Burghard, Luca Cosmo, Alexander Dieckmann, Reinhard Klein, Yusuf Sahillioglu
2016 J jnl
Non-Rigid Puzzles.
Comput. Graph. Forum
Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers
2016 B conf
Palmprint recognition via discriminative index learning.
ICPR
Jan Svoboda, Jonathan Masci, Michael M. Bronstein
2016 — conf
Partial Matching of Deformable Shapes.
3DOR@Eurographics
Luca Cosmo, Emanuele Rodolà, Michael M. Bronstein, Andrea Torsello, Daniel Cremers, Yusuf Sahillioglu
2016 J jnl
Recent Trends, Applications, and Perspectives in 3D Shape Similarity Assessment.
Comput. Graph. Forum
Silvia Biasotti, Andrea Cerri, Alexander M. Bronstein, Michael M. Bronstein
2016 — conf
Shape Analysis with Anisotropic Windowed Fourier Transform.
3DV
Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein
2016 J jnl
Shape Retrieval of Non-rigid 3D Human Models.
Int. J. Comput. Vis.
David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, Long Lai, Bo Li, Chen-Feng Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Li Sun, Gary K. L. Tam, Atsushi Tatsuma, Jianbo Ye
2016 — ch.
Sparse Models for Intrinsic Shape Correspondence.
Perspectives in Shape Analysis
Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro
2015 — ed.
36th Annual Conference of the European Association for Computer Graphics, Eurographics 2015 - Education Papers, Zurich, Switzerland, May 4-8, 2015
Eurographics (Education Papers)
Matthias Teschner, Michael M. Bronstein
2015 — ed.
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part I
ECCV Workshops (1)
Lourdes Agapito, Michael M. Bronstein, Carsten Rother
2015 — ed.
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II
ECCV Workshops (2)
Lourdes Agapito, Michael M. Bronstein, Carsten Rother
2015 — ed.
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part III
ECCV Workshops (3)
Lourdes Agapito, Michael M. Bronstein, Carsten Rother
2015 — ed.
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part IV
ECCV Workshops (4)
Lourdes Agapito, Michael M. Bronstein, Carsten Rother
2015 — conf
Contactless biometric hand geometry recognition using a low-cost 3D camera.
ICB
Jan Svoboda, Michael M. Bronstein, Martin Drahanský
2015 A* conf
Functional correspondence by matrix completion.
CVPR
Artiom Kovnatsky, Michael M. Bronstein, Xavier Bresson, Pierre Vandergheynst
2015 — conf
Geodesic Convolutional Neural Networks on Riemannian Manifolds.
ICCV Workshops
Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst
2015 J jnl
Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks.
Comput. Graph. Forum
Davide Boscaini, Jonathan Masci, Simone Melzi, Michael M. Bronstein, Umberto Castellani, Pierre Vandergheynst
2015 J jnl
MADMM: a generic algorithm for non-smooth optimization on manifolds.
CoRR
Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein
2015 — ch.
Manifold Intrinsic Similarity.
Handbook of Mathematical Methods in Imaging
Alexander M. Bronstein, Michael M. Bronstein
2015 J jnl
Multimodal Manifold Analysis by Simultaneous Diagonalization of Laplacians.
IEEE Trans. Pattern Anal. Mach. Intell.
Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein, Klaus Glashoff, Alexander M. Bronstein
2015 J jnl
Partial Functional Correspondence.
CoRR
Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers
2015 A* conf
Robust Principal Component Analysis on Graphs.
ICCV
Nauman Shahid, Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst
2015 J jnl
Robust Principal Component Analysis on Graphs.
CoRR
Nauman Shahid, Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst
2015 J jnl
Shape-from-Operator: Recovering Shapes from Intrinsic Operators.
Comput. Graph. Forum
Davide Boscaini, Davide Eynard, Drosos Kourounis, Michael M. Bronstein
2015 J jnl
ShapeNet: Convolutional Neural Networks on Non-Euclidean Manifolds.
CoRR
Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst
2014 — conf
Coulomb Shapes: Using Electrostatic Forces for Deformation-invariant Shape Representation.
3DOR@Eurographics
Davide Boscaini, Ramunas Girdziusas, Michael M. Bronstein
2014 — ch.
Descriptor Learning for Omnidirectional Image Matching.
Registration and Recognition in Images and Videos
Jonathan Masci, Davide Migliore, Michael M. Bronstein, Jürgen Schmidhuber
2014 J jnl
Equi-affine Invariant Geometry for Shape Analysis.
J. Math. Imaging Vis.
Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Dan Waisman, Nir A. Sochen, Ron Kimmel
2014 B conf
Gamut mapping with image Laplacian commutators.
ICIP
Artiom Kovnatsky, Davide Eynard, Michael M. Bronstein
2014 J jnl
Laplacian colormaps: a framework for structure-preserving color transformations.
Comput. Graph. Forum
Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein
2014 J jnl
Matrix Completion on Graphs.
CoRR
Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst
2014 J jnl
Multimodal Similarity-Preserving Hashing.
IEEE Trans. Pattern Anal. Mach. Intell.
Jonathan Masci, Michael M. Bronstein, Alexander M. Bronstein, Jürgen Schmidhuber
2014 — conf
Quantifying 3D Shape Similarity Using Maps: Recent Trends, Applications and Perspectives.
Eurographics (State of the Art Reports)
Silvia Biasotti, Andrea Cerri, Alexander M. Bronstein, Michael M. Bronstein
2014 — conf
Shape Retrieval of Non-Rigid 3D Human Models.
3DOR@Eurographics
David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, Abdessamad Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, J. Han, Henry Johan, Long Lai, Bo Li, C. Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Atsushi Tatsuma, Jianbo Ye
2014 J jnl
Shape-from-intrinsic operator.
CoRR
Davide Boscaini, Davide Eynard, Michael M. Bronstein
2014 — conf
Sparse similarity-preserving hashing.
ICLR
Jonathan Masci, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro
2014 J jnl
Supervised learning of bag-of-features shape descriptors using sparse coding.
Comput. Graph. Forum
Roee Litman, Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani
2013 — ed.
18th International Workshop on Vision, Modeling, and Visualization, VMV 2013, Lugano, Switzerland, September 11-13, 2013
VMV
Michael M. Bronstein, Jean Favre, Kai Hormann
2013 J jnl
Almost-commuting matrices are almost jointly diagonalizable
CoRR
Klaus Glashoff, Michael M. Bronstein
2013 J jnl
Asymptotic metrics on the space of matrices under the commutation relation
CoRR
Klaus Glashoff, Michael M. Bronstein
2013 J jnl
Coupled quasi-harmonic bases.
Comput. Graph. Forum
Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Klaus Glashoff, Ron Kimmel
2013 — ch.
Group-Valued Regularization for Motion Segmentation of Articulated Shapes.
Innovations for Shape Analysis, Models and Algorithms
Guy Rosman, Michael M. Bronstein, Alexander M. Bronstein, Alon Wolf, Ron Kimmel
2013 J jnl
Heat kernel coupling for multiple graph analysis.
CoRR
Michael M. Bronstein, Klaus Glashoff
2013 Misc conf
Learnable low rank sparse models for speech denoising.
ICASSP
Pablo Sprechmann, Alexander M. Bronstein, Michael M. Bronstein, Guillermo Sapiro
2013 J jnl
Making Laplacians commute.
CoRR
Michael M. Bronstein, Klaus Glashoff, Terry A. Loring
2013 J jnl
Sparse Modeling of Intrinsic Correspondences.
Comput. Graph. Forum
Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro
2013 — ch.
Stable Semi-local Features for Non-rigid Shapes.
Innovations for Shape Analysis, Models and Algorithms
Roee Litman, Alexander M. Bronstein, Michael M. Bronstein
2013 J jnl
Structure-preserving color transformations using Laplacian commutativity.
CoRR
Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein
2012 — ed.
5th Eurographics Workshop on 3D Object Retrieval, 3DOR@Eurographics 2012, Cagliari, Sardinia, Italy, May 13, 2012
3DOR@Eurographics
Michela Spagnuolo, Michael M. Bronstein, Alexander M. Bronstein, Alfredo Ferreira
2012 — conf
Affine-Invariant Photometric Heat Kernel Signatures.
3DOR@Eurographics
Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Dan Raviv, Ron Kimmel
2012 — conf
Articulated Motion Segmentation of Point Clouds by Group-Valued Regularization.
3DOR@Eurographics
Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2012 — conf
Diffusion Geometry in Shape Analysis.
Eurographics (Tutorials)
Michael M. Bronstein, Umberto Castellani, Alexander M. Bronstein
2012 — ch.
Feature-Based Methods in 3D Shape Analysis.
3D Imaging, Analysis and Applications
Alexander M. Bronstein, Michael M. Bronstein, Maks Ovsjanikov
2012 — conf
Group-Valued Regularization for Analysis of Articulated Motion.
ECCV Workshops (1)
Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Xue-Cheng Tai, Ron Kimmel
2012 A* conf
Intrinsic shape context descriptors for deformable shapes.
CVPR
Iasonas Kokkinos, Michael M. Bronstein, Roee Litman, Alexander M. Bronstein
2012 J jnl
LDAHash: Improved Matching with Smaller Descriptors.
IEEE Trans. Pattern Anal. Mach. Intell.
Christoph Strecha, Alexander M. Bronstein, Michael M. Bronstein, Pascal Fua
2012 J jnl
Motion-based mesh segmentation using augmented silhouettes.
Graph. Model.
Stefano Marras, Michael M. Bronstein, Kai Hormann, Riccardo Scateni, Roberto Scopigno
2012 J jnl
Multimodal diffusion geometry by joint diagonalization of Laplacians
CoRR
Davide Eynard, Klaus Glashoff, Michael M. Bronstein, Alexander M. Bronstein
2012 J jnl
Multimodal similarity-preserving hashing
CoRR
Jonathan Masci, Michael M. Bronstein, Alexander M. Bronstein, Jürgen Schmidhuber
2012 — conf
Putting the Pieces Together: Regularized Multi-part Shape Matching.
ECCV Workshops (1)
Or Litany, Alexander M. Bronstein, Michael M. Bronstein
2012 — ed.
Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 - June 2, 2011, Revised Selected Papers
SSVM
Alfred M. Bruckstein, Bart M. ter Haar Romeny, Alexander M. Bronstein, Michael M. Bronstein
2012 J jnl
Sparse Modeling of Intrinsic Correspondences
CoRR
Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro
2012 — conf
Stable Spectral Mesh Filtering.
ECCV Workshops (1)
Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein
2012 J jnl
Stable volumetric features in deformable shapes.
Comput. Graph.
Roee Litman, Alexander M. Bronstein, Michael M. Bronstein
2012 — conf
Structure from Motion Using Augmented Lagrangian Robust Factorization.
3DIMPVT
Klaus Glashoff, Michael M. Bronstein
2011 — conf
A Correspondence-Less Approach to Matching of Deformable Shapes.
SSVM
Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein
2011 J jnl
A correspondence-less approach to matching of deformable shapes
CoRR
Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein
2011 A* conf
Affine-invariant diffusion geometry for the analysis of deformable 3D shapes.
CVPR
Dan Raviv, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel, Nir A. Sochen
2011 J jnl
Affine-invariant geodesic geometry of deformable 3D shapes.
Comput. Graph.
Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen
2011 J jnl
Are MSER Features Really Interesting?
IEEE Trans. Pattern Anal. Mach. Intell.
Ron Kimmel, Cuiping Zhang, Alexander M. Bronstein, Michael M. Bronstein
2011 — conf
Boosted metric learning for 3D multi-modal deformable registration.
ISBI
Fabrice Michel, Michael M. Bronstein, Alexander M. Bronstein, Nikos Paragios
2011 — conf
Deformable Shape Retrieval by Learning Diffusion Kernels.
SSVM
Yonathan Aflalo, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2011 J jnl
Descriptor learning for omnidirectional image matching
CoRR
Jonathan Masci, Davide Migliore, Michael M. Bronstein, Jürgen Schmidhuber
2011 J jnl
Diffusion framework for geometric and photometric data fusion in non-rigid shape analysis
CoRR
Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel
2011 J jnl
Diffusion-geometric maximally stable component detection in deformable shapes.
Comput. Graph.
Roee Litman, Alexander M. Bronstein, Michael M. Bronstein
2011 — conf
Discrete Minimum Distortion Correspondence Problems for Non-rigid Shape Matching.
SSVM
Chaohui Wang, Michael M. Bronstein, Alexander M. Bronstein, Nikos Paragios
2011 — conf
Equi-affine Invariant Geometries of Articulated Objects.
Theoretical Foundations of Computer Vision
Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen
2011 — conf
Group-Valued Regularization Framework for Motion Segmentation of Dynamic Non-rigid Shapes.
SSVM
Guy Rosman, Michael M. Bronstein, Alexander M. Bronstein, Alon Wolf, Ron Kimmel
2011 J jnl
Kernel diff-hash
CoRR
Michael M. Bronstein
2011 J jnl
Lazy Sliding Window Implementation of the Bilateral Filter on Parallel Architectures.
IEEE Trans. Image Process.
Michael M. Bronstein
2011 J jnl
Multimodal diff-hash
CoRR
Michael M. Bronstein
2011 — conf
Photometric Heat Kernel Signatures.
SSVM
Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel
2011 — conf
SHREC '11: Robust Feature Detection and Description Benchmark.
3DOR@Eurographics
Edmond Boyer, Alexander M. Bronstein, Michael M. Bronstein, Benjamin Bustos, Tal Darom, Radu Horaud, Ingrid Hotz, Yosi Keller, Johannes Keustermans, Artiom Kovnatsky, Roee Litman, Jan Reininghaus, Ivan Sipiran, Dirk Smeets, Paul Suetens, Dirk Vandermeulen, Andrei Zaharescu, Valentin Zobel
2011 J jnl
SHREC 2011: robust feature detection and description benchmark
CoRR
Edmond Boyer, Alexander M. Bronstein, Michael M. Bronstein, Benjamin Bustos, Tal Darom, Radu Horaud, Ingrid Hotz, Yosi Keller, Johannes Keustermans, Artiom Kovnatsky, Roee Litman, Jan Reininghaus, Ivan Sipiran, Dirk Smeets, Paul Suetens, Dirk Vandermeulen, Andrei Zaharescu, Valentin Zobel
2011 — conf
Shape Palindromes: Analysis of Intrinsic Symmetries in 2D Articulated Shapes.
SSVM
Amit Hooda, Michael M. Bronstein, Alexander M. Bronstein, Radu Horaud
2011 J jnl
Shape Recognition with Spectral Distances.
IEEE Trans. Pattern Anal. Mach. Intell.
Michael M. Bronstein, Alexander M. Bronstein
2011 J jnl
Shape google: Geometric words and expressions for invariant shape retrieval.
ACM Trans. Graph.
Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas, Maks Ovsjanikov
2010 J jnl
A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching.
Int. J. Comput. Vis.
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Mona Mahmoudi, Guillermo Sapiro
2010 J jnl
Affine-invariant diffusion geometry for the analysis of deformable 3D shapes
CoRR
Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen
2010 J jnl
Affine-invariant geodesic geometry of deformable 3D shapes
CoRR
Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen
2010 A* conf
Data fusion through cross-modality metric learning using similarity-sensitive hashing.
CVPR
Michael M. Bronstein, Alexander M. Bronstein, Fabrice Michel, Nikos Paragios
2010 J jnl
Diffusion-geometric maximally stable component detection in deformable shapes
CoRR
Roee Litman, Alexander M. Bronstein, Michael M. Bronstein
2010 J jnl
Full and Partial Symmetries of Non-rigid Shapes.
Int. J. Comput. Vis.
Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2010 — conf
Intrinsic Regularity Detection in 3D Geometry.
ECCV (3)
Niloy J. Mitra, Alexander M. Bronstein, Michael M. Bronstein
2010 J jnl
Nonlinear Dimensionality Reduction by Topologically Constrained Isometric Embedding.
Int. J. Comput. Vis.
Guy Rosman, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel
2010 — conf
SHREC'10 Track: Correspondence Finding.
3DOR@Eurographics
Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, Anastasia Dubrovina, Leonidas J. Guibas, Radu Horaud, Ron Kimmel, David Knossow, Etienne von Lavante, Diana Mateus, Maks Ovsjanikov, Avinash Sharma
2010 — conf
SHREC'10 Track: Feature Detection and Description.
3DOR@Eurographics
Alexander M. Bronstein, Michael M. Bronstein, Benjamin Bustos, Umberto Castellani, Marco Cristani, Bianca Falcidieno, Leonidas J. Guibas, Iasonas Kokkinos, Vittorio Murino, Maks Ovsjanikov, Giuseppe Patanè, Ivan Sipiran, Michela Spagnuolo, Jian Sun
2010 — conf
SHREC'10 Track: Robust Shape Retrieval.
3DOR@Eurographics
Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, Bianca Falcidieno, Andrea Fusiello, Afzal Godil, Leonidas J. Guibas, Iasonas Kokkinos, Zhouhui Lian, Maks Ovsjanikov, Giuseppe Patanè, Michela Spagnuolo, Roberto Toldo
2010 A* conf
Scale-invariant heat kernel signatures for non-rigid shape recognition.
CVPR
Michael M. Bronstein, Iasonas Kokkinos
2010 — conf
Spatially-Sensitive Affine-Invariant Image Descriptors.
ECCV (2)
Alexander M. Bronstein, Michael M. Bronstein
2010 J jnl
The Video Genome
CoRR
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2010 — conf
Volumetric heat kernel signatures.
3DOR@MM
Dan Raviv, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel
2009 — conf
3D-color video camera.
ICCV Workshops
O. Rubinstein, Yaron Honen, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2009 — book
Numerical Geometry of Non-Rigid Shapes
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2009 — conf
On reconstruction of non-rigid shapes with intrinsic regularization.
ICCV Workshops
Yohai S. Devir, Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2009 J jnl
Partial Similarity of Objects, or How to Compare a Centaur to a Horse.
Int. J. Comput. Vis.
Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel
2009 J jnl
Partial Similarity of Shapes Using a Statistical Significance Measure.
IPSJ Trans. Comput. Vis. Appl.
Alexander M. Bronstein, Michael M. Bronstein, Yair Carmon, Ron Kimmel
2009 — conf
Shape Google: a computer vision approach to isometry invariant shape retrieval.
ICCV Workshops
Maks Ovsjanikov, Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas
2009 J jnl
Topology-Invariant Similarity of Nonrigid Shapes.
Int. J. Comput. Vis.
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2008 J jnl
Analysis of Two-Dimensional Non-Rigid Shapes.
Int. J. Comput. Vis.
Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel
2008 — conf
Not only size matters: Regularized partial matching of nonrigid shapes.
CVPR Workshops
Alexander M. Bronstein, Michael M. Bronstein
2008 J jnl
Parallel algorithms for approximation of distance maps on parametric surfaces.
ACM Trans. Graph.
Ofir Weber, Yohai S. Devir, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2008 — conf
Regularized Partial Matching of Rigid Shapes.
ECCV (2)
Alexander M. Bronstein, Michael M. Bronstein
2007 J jnl
Calculus of Nonrigid Surfaces for Geometry and Texture Manipulation.
IEEE Trans. Vis. Comput. Graph.
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2007 J jnl
Expression-Invariant Representations of Faces.
IEEE Trans. Image Process.
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2007 — —
Isometry-invariant surface matching: numerical algorithms and applications.
Michael M. Bronstein
2007 — conf
Paretian Similarity for Partial Comparison of Non-rigid Objects.
SSVM
Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel
2007 A* conf
Rock, Paper, and Scissors: extrinsic vs. intrinsic similarity of non-rigid shapes.
ICCV
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2007 A* conf
Symmetries of non-rigid shapes.
ICCV
Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2007 J jnl
Weighted distance maps computation on parametric three-dimensional manifolds.
J. Comput. Phys.
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2006 J jnl
Efficient Computation of Isometry-Invariant Distances Between Surfaces.
SIAM J. Sci. Comput.
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2006 — conf
Facetoface: An Isometric Model for Facial Animation.
AMDO
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2006 — conf
Matching Two-Dimensional Articulated Shapes Using Generalized Multidimensional Scaling.
AMDO
Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel
2006 J jnl
Multigrid multidimensional scaling.
Numer. Linear Algebra Appl.
Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel, Irad Yavneh
2006 — conf
On Separation of Semitransparent Dynamic Images from Static Background.
ICA
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky
2006 — conf
Robust Expression-Invariant Face Recognition from Partially Missing Data.
ECCV (3)
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2006 — conf
Topologically Constrained Isometric Embedding.
Human Motion
Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2005 — conf
"Unmixing" tissues: sparse component analysis in multi-contrast MRI.
ICIP (2)
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2005 J jnl
Blind deconvolution of images using optimal sparse representations.
IEEE Trans. Image Process.
Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2005 — conf
Blind separation of tissues in multi-modal MRI using Sparse Component Analysis.
EUSIPCO
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2005 — conf
Expression-invariant face recognition via spherical embedding.
ICIP (3)
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2005 — conf
Isometric Embedding of Facial Surfaces into.
Scale-Space
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2005 J jnl
Quasi maximum likelihood MIMO blind deconvolution: Super- and sub-Gaussianity versus consistency.
IEEE Trans. Signal Process.
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky
2005 J jnl
Relative optimization for blind deconvolution.
IEEE Trans. Signal Process.
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky
2005 J jnl
Sparse ICA for blind separation of transmitted and reflected images.
Int. J. Imaging Syst. Technol.
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2005 J jnl
Three-Dimensional Face Recognition.
Int. J. Comput. Vis.
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2004 — conf
Blind Deconvolution Using the Relative Newton Method.
ICA
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky
2004 — conf
Blind Source Separation Using the Block-Coordinate Relative Newton Method.
ICA
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky
2004 J jnl
Blind source separation using block-coordinate relative Newton method.
Signal Process.
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky
2004 — conf
Face Recognition from Facial Surface Metric.
ECCV (2)
Alexander M. Bronstein, Michael M. Bronstein, Alon Spira, Ron Kimmel
2004 B conf
Fast relative newton algorithm for blind deconvolution of images.
ICIP
Alexander M. Bronstein, Michael Zibulevsky, Michael M. Bronstein, Yehoshua Y. Zeevi
2004 B conf
Fusion of 2D and 3D data in three-dimensional face recognition.
ICIP
Alexander M. Bronstein, Michael M. Bronstein, Eyal Gordon, Ron Kimmel
2004 — conf
Optimal Sparse Representations for Blind Deconvolution of Images.
ICA
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2004 B conf
Optimal sparse representations for blind source separation and blind deconvolution: a learning approach.
ICIP
Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2004 — conf
QML Blind Deconvolution: Asymptotic Analysis.
ICA
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2004 — conf
Quasi-Maximum Likelihood Blind Deconvolution of Images Acquired Through Scattering Media.
ISBI
Michael M. Bronstein, Alexander M. Bronstein, Yehoshua Y. Zeevi, Michael Zibulevsky
2003 — conf
Expression-Invariant 3D Face Recognition.
AVBPA
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2003 — conf
Separation of reflections via sparse ICA.
ICIP (1)
Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2003 — conf
Separation of semireflective layers using sparse ICA.
ICASSP (3)
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2002 — conf
Iterative reconstruction in diffraction tomography using nonuniform fast Fourier transform.
ISBI
Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky
2002 — conf
Optimal nonlinear estimation of photon coordinates in PET.
ISBI
Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi
2002 J jnl
Reconstruction in Diffraction Ultrasound Tomography Using Non-Uniform FFT.
IEEE Trans. Medical Imaging
Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Haim Azhari