Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs

9 February 2022

Cristian Bodnar

Francesco Di Giovanni

Papers citing "Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs"

36 / 36 papers shown

Title
Hypergraph Neural Sheaf Diffusion: A Symmetric Simplicial Set Framework for Higher-Order Learning Seongjin Choi Gahee Kim Yong-Geun Oh 26 0 0 09 May 2025
Understanding GNNs and Homophily in Dynamic Node Classification Michael Ito Danai Koutra Jenna Wiens 87 1 0 29 Apr 2025
Higher-Order Topological Directionality and Directed Simplicial Neural Networks M. Lecha Andrea Cavallo Francesca Dominici Elvin Isufi Claudio Battiloro AI4CE 151 2 0 17 Jan 2025
Enhancing Graph Representation Learning with Localized Topological Features Zuoyu Yan Qi Zhao Ze Ye Tengfei Ma Liangcai Gao Zhi Tang Yusu Wang Chao Chen 47 0 0 17 Jan 2025
Knowledge Planning in Large Language Models for Domain-Aligned Counseling Summarization Aseem Srivastava Smriti Joshi Tanmoy Chakraborty Md. Shad Akhtar 37 3 0 23 Sep 2024
Exploring the Potential of Large Language Models for Heterophilic Graphs Yuxia Wu Shujie Li Yuan Fang Chuan Shi 44 1 0 26 Aug 2024
Graph Neural Reaction Diffusion Models Moshe Eliasof Eldad Haber Eran Treister DiffM AI4CE 35 2 0 16 Jun 2024
Bundle Neural Networks for message diffusion on graphs Jacob Bamberger Federico Barbero Xiaowen Dong Michael M. Bronstein 39 1 0 24 May 2024
E(n) Equivariant Topological Neural Networks Claudio Battiloro Ege Karaismailoglu Mauricio Tec George Dasoulas Michelle Audirac Francesca Dominici 52 5 0 24 May 2024
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory Weichen Zhao Chenguang Wang Xinyan Wang Congying Han Tiande Guo Tianshu Yu 44 0 0 23 Feb 2024
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs M. Hanik Gabriele Steidl C. V. Tycowicz GNN MedIm 36 3 0 25 Jan 2024
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation Jialin Chen Yuelin Wang Cristian Bodnar Rex Ying Pietro Lió Yu Guang Wang 29 10 0 09 Nov 2023
Supercharging Graph Transformers with Advective Diffusion Qitian Wu Chenxiao Yang Kaipeng Zeng Fan Nie AI4CE 53 6 0 10 Oct 2023
Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks Andreas Roth Thomas Liebig 43 12 0 31 Aug 2023
The Expressive Power of Graph Neural Networks: A Survey Bingxue Zhang Changjun Fan Shixuan Liu Kuihua Huang Xiang Zhao Jin-Yu Huang Zhong Liu 40 19 0 16 Aug 2023
How Curvature Enhance the Adaptation Power of Framelet GCNs Dai Shi Yi Guo Zhiqi Shao Junbin Gao 26 14 0 19 Jul 2023
Evolving Computation Graphs Andreea Deac Jian Tang 22 1 0 22 Jun 2023
Graph Neural Convection-Diffusion with Heterophily Kai Zhao Qiyu Kang Yang Song Rui She Sijie Wang Wee Peng Tay 28 27 0 26 May 2023
Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion Dai Shi Zhiqi Shao Yi Guo Qianchuan Zhao Junbin Gao 34 1 0 25 May 2023
A Fractional Graph Laplacian Approach to Oversmoothing Sohir Maskey Raffaele Paolino Aras Bacho Gitta Kutyniok 27 29 0 22 May 2023
Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi Bertrand Charpentier Francesco Di Giovanni Fabrizio Frasca Stephan Günnemann Michael M. Bronstein 22 56 0 17 May 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks Weitao Du Yuanqi Du Limei Wang Dieqiao Feng Guifeng Wang Shuiwang Ji Carla P. Gomes Zhixin Ma AI4CE 32 33 0 07 Apr 2023
A Survey on Oversmoothing in Graph Neural Networks T. Konstantin Rusch Michael M. Bronstein Siddhartha Mishra 26 185 0 20 Mar 2023
Graph Neural Networks in Vision-Language Image Understanding: A Survey Henry Senior Greg Slabaugh Shanxin Yuan Luca Rossi GNN 33 13 0 07 Mar 2023
A critical look at the evaluation of GNNs under heterophily: Are we really making progress? Oleg Platonov Denis Kuznedelev Michael Diskin Artem Babenko Liudmila Prokhorenkova 31 188 0 22 Feb 2023
Revisiting Heterophily For Graph Neural Networks Sitao Luan Chenqing Hua Qincheng Lu Jiaqi Zhu Mingde Zhao Shuyuan Zhang Xiaoming Chang Doina Precup 44 181 0 14 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 72 13 0 08 Oct 2022
Not too little, not too much: a theoretical analysis of graph (over)smoothing Nicolas Keriven 41 89 0 24 May 2022
Graph Anisotropic Diffusion Ahmed A. A. Elhag Gabriele Corso Hannes Stärk Michael M. Bronstein DiffM GNN 22 0 0 30 Apr 2022
GraphWorld: Fake Graphs Bring Real Insights for GNNs John Palowitch Anton Tsitsulin Brandon Mayer Bryan Perozzi GNN 195 68 0 28 Feb 2022
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks Moshe Eliasof Ben Bodner Eran Treister GNN 35 7 0 10 Oct 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 94 562 0 04 Jan 2021
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs P. D. Haan Maurice Weiler Taco S. Cohen Max Welling 102 127 0 11 Mar 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 916 0 02 Mar 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,078 0 13 Feb 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 148 837 0 28 Sep 2019