Frasca, Fabrizio

19 publications

ICML 2025 Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca

NeurIPS 2025 Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT Guy Bar-Shalom, Fabrizio Frasca, Yaniv Galron, Yftah Ziser, Haggai Maron

ICLRW 2025 Learning on LLM Output Signatures for Gray Box LLM Behavior Analysis Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron

ICML 2025 Position: Graph Learning Will Lose Relevance Due to Poor Benchmarks 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

ICLR 2025 Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron

ECML-PKDD 2025 Understanding and Improving Laplacian Positional Encodings for Temporal GNNs Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof

NeurIPS 2024 A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron

NeurIPSW 2024 Efficient Subgraph GNNs via Graph Products and Coarsening Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron

ICML 2024 Position: Future Directions in the Theory of Graph Machine Learning Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

NeurIPSW 2024 Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron

NeurIPSW 2024 Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron

LoG 2023 Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein

ICLR 2023 Graph Neural Networks for Link Prediction with Subgraph Sketching Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire

ICML 2023 Graph Positional Encoding via Random Feature Propagation Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

ICLR 2022 Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

NeurIPS 2022 Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries Fabrizio Frasca, Beatrice Bevilacqua, Michael Bronstein, Haggai Maron

NeurIPS 2021 Weisfeiler and Lehman Go Cellular: CW Networks Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montufar, Michael Bronstein

ICML 2021 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F Montufar, Pietro Lió, Michael Bronstein

ICLRW 2021 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montufar, Pietro Liò, Michael M. Bronstein