Revisiting Generalized p-Laplacian Regularized Framelet GCNs:
Convergence, Energy Dynamic and Training with Non-Linear Diffusion

Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion

25 May 2023

Dai Shi

Junbin Gao

Papers citing "Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion"

9 / 9 papers shown

Title
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond Zhiqi Shao Dai Shi Andi Han Yi Guo Qianchuan Zhao Junbin Gao 11 11 0 06 Sep 2023
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 64 13 0 08 Oct 2022
Optimization-Induced Graph Implicit Nonlinear Diffusion Qi Chen Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin DiffM 42 32 0 29 Jun 2022
How Powerful are Spectral Graph Neural Networks Xiyuan Wang Muhan Zhang 70 175 0 23 May 2022
A Simple Yet Effective SVD-GCN for Directed Graphs Chunya Zou Andi Han Lequan Lin Junbin Gao GNN 45 7 0 19 May 2022
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 163 1,095 0 27 Apr 2021
How Framelets Enhance Graph Neural Networks Xuebin Zheng Bingxin Zhou Junbin Gao Yu Guang Wang Pietro Lió Ming Li Guido Montúfar 48 69 0 13 Feb 2021
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 167 1,058 0 13 Feb 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 226 1,726 0 09 Jun 2018