Joint Diffusion Processes as an Inductive Bias in Sheaf Neural Networks

30 July 2024

Papers citing "Joint Diffusion Processes as an Inductive Bias in Sheaf Neural Networks"

10 / 10 papers shown

Title
Nonlinear Sheaf Diffusion in Graph Neural Networks Olga Zaghen 66 1 0 01 Mar 2024
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond Oleg Platonov Denis Kuznedelev Artem Babenko Liudmila Prokhorenkova 68 41 0 13 Sep 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 62 175 0 09 Feb 2022
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks Yujun Yan Milad Hashemi Kevin Swersky Yaoqing Yang Danai Koutra 82 250 0 12 Feb 2021
Sheaf Neural Networks J. Hansen Thomas Gebhart GNN 31 40 0 08 Dec 2020
Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View Deli Chen Yankai Lin Wei Li Peng Li Jie Zhou Xu Sun 70 1,096 0 07 Sep 2019
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters Hoang NT Takanori Maehara GNN 73 427 0 23 May 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 669 5,457 0 20 Dec 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 361 19,991 0 30 Oct 2017
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 501 28,901 0 09 Sep 2016