Publications
How does over-squashing affect the power of GNNs? [PDF]
Francesco Di Giovanni*, T. K. Rusch*, et al.,
Preprint, Jun. 2023
DRew: Dynamically Rewired Message Passing with Delay? [PDF]
B. Gutteridge, X. Dong, M. Bronstein, Francesco Di Giovanni,
ICML23
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology [PDF]
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael Bronstein
ICML23
Understanding convolutions on graphs via energies [PDF]
Francesco Di Giovanni*, James Rowbottom*, Benjamin Chamberlain, Thomas Markovich, Michael Bronstein
TMLR, 2023
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs [PDF] [Blog] [Video by Aleksa Gordić]
Cristian Bodnar, Francesco Di Giovanni, Benjamin Chamberlain, Pietro Liò, Michael Bronstein
NeurIPS2022
Heterogeneous manifolds for curvature-aware graph embedding [PDF]
Francesco Di Giovanni*, Giulia Luise*, Michael Bronstein
Preprint, Feb. 2022
Understanding over-squashing and bottlenecks on graphs via curvature [PDF] [Blog] [Video by Aleksa Gordić]
Jake Topping*, Francesco Di Giovanni*, Benjamin Chamberlain, Xiaowen Dong, Michael Bronstein
Outstanding paper Honorable mention , ICLR 2022 (oral)
