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Publication search results
found 367 matches
- 2024
- Gbètondji J.-S. Dovonon, Michael M. Bronstein, Matt J. Kusner:
Setting the Record Straight on Transformer Oversmoothing. CoRR abs/2401.04301 (2024) - Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka:
Future Directions in Foundations of Graph Machine Learning. CoRR abs/2402.02287 (2024) - Xingyue Huang, Miguel A. Romero Orth, Pablo Barceló, Michael M. Bronstein, Ismail Ilkan Ceylan:
Link Prediction with Relational Hypergraphs. CoRR abs/2402.04062 (2024) - Chen Lin, Liheng Ma, Yiyang Chen, Wanli Ouyang, Michael M. Bronstein, Philip H. S. Torr:
Revealing Decurve Flows for Generalized Graph Propagation. CoRR abs/2402.08480 (2024) - Emily Jin, Michael Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger:
Homomorphism Counts for Graph Neural Networks: All About That Basis. CoRR abs/2402.08595 (2024) - Theodore Papamarkou, Tolga Birdal, Michael Bronstein, Gunnar 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:
Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR abs/2402.08871 (2024) - 2023
- Kamilia Zaripova
, Luca Cosmo
, Anees Kazi, Seyed-Ahmad Ahmadi
, Michael M. Bronstein, Nassir Navab
:
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications. Medical Image Anal. 88: 102839 (2023) - Giorgos Bouritsas
, Fabrizio Frasca, Stefanos Zafeiriou
, Michael M. Bronstein:
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 657-668 (2023) - Anees Kazi
, Luca Cosmo
, Seyed-Ahmad Ahmadi
, Nassir Navab
, Michael M. Bronstein:
Differentiable Graph Module (DGM) for Graph Convolutional Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1606-1617 (2023) - Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli:
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. AAAI 2023: 9251-9259 - Edoardo Cetin, Benjamin Paul Chamberlain, Michael M. Bronstein, Jonathan J. Hunt:
Hyperbolic Deep Reinforcement Learning. ICLR 2023 - Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire:
Graph Neural Networks for Link Prediction with Subgraph Sketching. ICLR 2023 - T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra:
Gradient Gating for Deep Multi-Rate Learning on Graphs. ICLR 2023 - Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein:
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. ICML 2023: 7865-7885 - Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni:
DRew: Dynamically Rewired Message Passing with Delay. ICML 2023: 12252-12267 - Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein:
Edge Directionality Improves Learning on Heterophilic Graphs. LoG 2023: 25 - Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. NeurIPS 2023 - Joshua Southern, Jeremy Wayland, Michael Bronstein, Bastian Rieck:
Curvature Filtrations for Graph Generative Model Evaluation. NeurIPS 2023 - Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni:
Can strong structural encoding reduce the importance of Message Passing? TAG-ML 2023: 278-288 - Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck
:
Curvature Filtrations for Graph Generative Model Evaluation. CoRR abs/2301.12906 (2023) - Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio', Michael M. Bronstein:
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. CoRR abs/2302.02941 (2023) - T. Konstantin Rusch, Michael M. Bronstein, Siddhartha Mishra:
A Survey on Oversmoothing in Graph Neural Networks. CoRR abs/2303.10993 (2023) - Tsachi Blau, Roy Ganz, Chaim Baskin, Michael Elad, Alexander M. Bronstein:
Classifier Robustness Enhancement Via Test-Time Transformation. CoRR abs/2303.15409 (2023) - Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni:
DRew: Dynamically Rewired Message Passing with Delay. CoRR abs/2305.08018 (2023) - Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein:
Edge Directionality Improves Learning on Heterophilic Graphs. CoRR abs/2305.10498 (2023) - Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo:
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module. CoRR abs/2305.16174 (2023) - Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic:
How does over-squashing affect the power of GNNs? CoRR abs/2306.03589 (2023) - Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein:
On the Impact of Sample Size in Reconstructing Graph Signals. CoRR abs/2307.00336 (2023) - Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. CoRR abs/2307.01026 (2023) - António Leitão, Maxime Lucas, Simone Poetto, Taylor A. Hersh, Shane Gero, David F. Gruber, Michael M. Bronstein, Giovanni Petri:
Social learning across symbolic cultural barriers in non-human cultures. CoRR abs/2307.05304 (2023)
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