Francesco Di Giovanni

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 24

Top Topics

Graph Embedding

Message Passing

Top Venues

Trans. Mach. Learn. Res.

Publications

Nian Liu, Xiaoxin He, Thomas Laurent, Francesco Di Giovanni, Michael M. Bronstein, Xavier Bresson
Advancing Graph Convolutional Networks via General Spectral Wavelets. CoRR (2024)
Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni
Locality-Aware Graph Rewiring in GNNs. ICLR (2024)
Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni
Metric Flow Matching for Smooth Interpolations on the Data Manifold. CoRR (2024)
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? Trans. Mach. Learn. Res. 2024 (2024)
Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer
Understanding Virtual Nodes: Oversmoothing, Oversquashing, and Node Heterogeneity. CoRR (2024)
Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni
Can strong structural encoding reduce the importance of Message Passing? TAG-ML (2023)
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
DRew: Dynamically Rewired Message Passing with Delay. ICML (2023)
Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni
Locality-Aware Graph-Rewiring in GNNs. CoRR (2023)
Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni
Can strong structural encoding reduce the importance of Message Passing? CoRR (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)
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
DRew: Dynamically Rewired Message Passing with Delay. CoRR (2023)
Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein
Understanding convolution on graphs via energies. Trans. Mach. Learn. Res. 2023 (2023)
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
Edge Directionality Improves Learning on Heterophilic Graphs. CoRR (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 (2023)
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
Edge Directionality Improves Learning on Heterophilic Graphs. LoG (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 (2023)
Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. NeurIPS (2022)
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
Understanding over-squashing and bottlenecks on graphs via curvature. ICLR (2022)
Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Liò, Michael M. Bronstein
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. CoRR (2022)
Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein
Graph Neural Networks as Gradient Flows. CoRR (2022)
Francesco Di Giovanni, Giulia Luise, Michael M. Bronstein
Heterogeneous manifolds for curvature-aware graph embedding. CoRR (2022)
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
Understanding over-squashing and bottlenecks on graphs via curvature. CoRR (2021)
Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
Beltrami Flow and Neural Diffusion on Graphs. CoRR (2021)
Ben Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
Beltrami Flow and Neural Diffusion on Graphs. NeurIPS (2021)