Fabrizio Frasca

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Subgraph Isomorphism

Top Venues

Publications

Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron
A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening. CoRR (2024)
Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael Bronstein, Martin Grohe, Stefanie Jegelka
Future Directions in Foundations of Graph Machine Learning. CoRR (2024)
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)
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
Edge Directionality Improves Learning on Heterophilic Graphs. CoRR (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) (2023)
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
Graph Positional Encoding via Random Feature Propagation. ICML (2023)
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
Edge Directionality Improves Learning on Heterophilic Graphs. LoG (2023)
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
Graph Positional Encoding via Random Feature Propagation. CoRR (2023)
Fabrizio Frasca, Matteo Matteucci, Michele Leone, Marco J. Morelli, Marco Masseroli
Accurate and highly interpretable prediction of gene expression from histone modifications. BMC Bioinform. 23 (1) (2022)
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
Equivariant Subgraph Aggregation Networks. ICLR (2022)
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. NeurIPS (2022)
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Hammerla, Michael M. Bronstein, Max Hansmire
Graph Neural Networks for Link Prediction with Subgraph Sketching. CoRR (2022)
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. CoRR (2022)
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein
Weisfeiler and Lehman Go Cellular: CW Networks. NeurIPS (2021)
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael M. Bronstein
Weisfeiler and Lehman Go Cellular: CW Networks. CoRR (2021)
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
Equivariant Subgraph Aggregation Networks. CoRR (2021)
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael M. Bronstein
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. CoRR (2021)
Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. ICML (2021)
Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, Michael M. Bronstein
Temporal Graph Networks for Deep Learning on Dynamic Graphs. CoRR (2020)
Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting. CoRR (2020)
Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti
SIGN: Scalable Inception Graph Neural Networks. CoRR (2020)
Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill A. Veselkov, Alberto Paccanaro, Michael M. Bronstein
Learning interpretable disease self-representations for drug repositioning. CoRR (2019)
Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein
Fake News Detection on Social Media using Geometric Deep Learning. CoRR (2019)
Fabrizio Frasca, Matteo Matteucci, Marco Masseroli, Marco J. Morelli
Modeling Gene Transcriptional Regulation by Means of Hyperplanes Genetic Clustering. IJCNN (2018)
Fabrizio Frasca, Matteo Matteucci, Marco J. Morelli, Marco Masseroli
Exposing and Characterizing Subpopulations of Distinctly Regulated Genes by K-Plane Regression. CIBB (2018)