Fabrizio Frasca

According to our database, Fabrizio Frasca authored at least 16 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Future Directions in Foundations of Graph Machine Learning.

Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

CoRR, 2024

2023

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.

Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Edge Directionality Improves Learning on Heterophilic Graphs.

Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein

CoRR, 2023

Graph Positional Encoding via Random Feature Propagation.

Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Accurate and highly interpretable prediction of gene expression from histone modifications.

Fabrizio Frasca, Matteo Matteucci, Michele Leone, Marco J. Morelli, Marco Masseroli

BMC Bioinform., 2022

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.

Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Equivariant Subgraph Aggregation Networks.

Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Weisfeiler and Lehman Go Cellular: CW Networks.

Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.

Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Temporal Graph Networks for Deep Learning on Dynamic Graphs.

Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, Michael M. Bronstein

CoRR, 2020

SIGN: Scalable Inception Graph Neural Networks.

Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti

CoRR, 2020

2019

Learning interpretable disease self-representations for drug repositioning.

Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill A. Veselkov, Alberto Paccanaro, Michael M. Bronstein

CoRR, 2019

Fake News Detection on Social Media using Geometric Deep Learning.

Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein

CoRR, 2019

2018

Modeling Gene Transcriptional Regulation by Means of Hyperplanes Genetic Clustering.

Fabrizio Frasca, Matteo Matteucci, Marco Masseroli, Marco J. Morelli

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Exposing and Characterizing Subpopulations of Distinctly Regulated Genes by K-Plane Regression.

Fabrizio Frasca, Matteo Matteucci, Marco J. Morelli, Marco Masseroli

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2018