Di Giovanni, Francesco

17 publications

ICML 2025 A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition Nian Liu, Xiaoxin He, Thomas Laurent, Francesco Di Giovanni, Michael M. Bronstein, Xavier Bresson

ICLRW 2025 Relaxed Equivariance via Multitask Learning Ahmed A. A. Elhag, T. Konstantin Rusch, Francesco Di Giovanni, Michael M. Bronstein

ICLR 2025 Understanding Virtual Nodes: Oversquashing and Node Heterogeneity Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer

TMLR 2024 How Does Over-Squashing Affect the Power of GNNs? Francesco Di Giovanni, T. Konstantin Rusch, Michael Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Veličković

ICLR 2024 Locality-Aware Graph Rewiring in GNNs Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni

NeurIPS 2024 Metric Flow Matching for Smooth Interpolations on the Data Manifold Kacper Kapuśniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael Bronstein, Avishek Joey Bose, Francesco Di Giovanni

ICMLW 2023 Can Strong Structural Encoding Reduce the Importance of Message Passing? Floor Eijkelboom, Erik J Bekkers, Michael M. Bronstein, Francesco Di Giovanni

ICML 2023 DRew: Dynamically Rewired Message Passing with Delay Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni

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

NeurIPSW 2023 How Does Over-Squashing Affect the Power of GNNs? Francesco Di Giovanni, T. Konstantin Rusch, Michael Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Veličković

ICML 2023 On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein

TMLR 2023 Understanding Convolution on Graphs via Energies Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein

ICLRW 2022 Heterogeneous Manifolds for Curvature-Aware Graph Embedding Francesco Di Giovanni, Giulia Luise, Michael M. Bronstein

ICLRW 2022 Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lio, Michael M. Bronstein

NeurIPS 2022 Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs Cristian Bodnar, Francesco Di Giovanni, Benjamin Chamberlain, Pietro Lió, Michael Bronstein

ICLR 2022 Understanding Over-Squashing and Bottlenecks on Graphs via Curvature Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein

NeurIPS 2021 Beltrami Flow and Neural Diffusion on Graphs Benjamin Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael Bronstein