Publications

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
Preprint, Feb. 2023

Graph Neural Networks as Gradient Flows [PDF]

Francesco Di Giovanni*, James Rowbottom*, Benjamin Chamberlain, Thomas Markovich, Michael Bronstein
Preprint, Jun. 2022

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)

Beltrami Flow and Neural Diffusion on Graphs [PDF] [Blog]

Benjamin Chamberlain*, James Rowbottom*, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael Bronstein
NeurIPS 2021

Convergence of Ricci flow solutions to Taub-NUT [PDF] [Arxiv]

Francesco Di Giovanni
Communications in Partial Differential Equations, Volume 46, 2021 - Issue 8

Rotationally symmetric Ricci flow on R^n+1 [PDF] [Arxiv]

Francesco Di Giovanni
Advances in Mathematics, Volume 381, 2021

Ricci flow of warped Berger metrics on R^4 [PDF] [Arxiv]

Francesco Di Giovanni
Calculus of Variations and Partial Differential Equations, Volume 59, 2020