Tangent Bundle Convolutional Learning: from Manifolds to Cellular
Sheaves and Back

Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back

20 March 2023

Claudio Battiloro

Zhiyang Wang

Paolo Di Lorenzo

Alejandro Ribeiro

Papers citing "Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back"

18 / 18 papers shown

Title
Topological Neural Networks over the Air Simone Fiorellino Claudio Battiloro Paolo Di Lorenzo 107 3 0 17 Feb 2025
Higher-Order Topological Directionality and Directed Simplicial Neural Networks Manuel Lecha Andrea Cavallo Francesca Dominici Elvin Isufi Claudio Battiloro AI4CE 193 4 0 17 Jan 2025
Bundle Neural Networks for message diffusion on graphs Jacob Bamberger Federico Barbero Xiaowen Dong Michael M. Bronstein 88 2 0 24 May 2024
E(n) Equivariant Topological Neural Networks Claudio Battiloro Ege Karaismailoglu Mauricio Tec George Dasoulas Michelle Audirac Francesca Dominici 84 9 0 24 May 2024
Cell Attention Networks Lorenzo Giusti Claudio Battiloro Lucia Testa P. Lorenzo S. Sardellitti Sergio Barbarossa 3DPC GNN 344 35 0 16 Sep 2022
Diffusion of Information on Networked Lattices by Gossip Hans Riess Robert Ghrist 34 10 0 01 Apr 2022
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs Cristian Bodnar Francesco Di Giovanni B. Chamberlain Pietro Lio Michael M. Bronstein 67 177 0 09 Feb 2022
Understanding over-squashing and bottlenecks on graphs via curvature Jake Topping Francesco Di Giovanni B. Chamberlain Xiaowen Dong M. Bronstein 101 442 0 29 Nov 2021
Sheaf Neural Networks J. Hansen Thomas Gebhart GNN 36 40 0 08 Dec 2020
Graphon Neural Networks and the Transferability of Graph Neural Networks Luana Ruiz Luiz F. O. Chamon Alejandro Ribeiro GNN 63 145 0 05 Jun 2020
$Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in $L^\infty$ from Random Samples$ Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in $L^\infty$ from Random Samples David B. Dunson Hau‐Tieng Wu Nan Wu 53 65 0 11 Dec 2019
Transferability of Spectral Graph Convolutional Neural Networks Ron Levie Wei Huang Lorenzo Bucci M. Bronstein Gitta Kutyniok GNN 93 128 0 30 Jul 2019
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 202 314 0 05 Nov 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 208 7,618 0 01 Oct 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 558 3,112 0 04 Jun 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas Guibas 3DH 3DPC 3DV PINN 430 14,259 0 02 Dec 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 647 3,273 0 24 Nov 2016
Vector Diffusion Maps and the Connection Laplacian A. Singer Hau-Tieng Wu 58 310 0 01 Feb 2011