Fast Haar Transforms for Graph Neural Networks

10 July 2019

Papers citing "Fast Haar Transforms for Graph Neural Networks"

9 / 9 papers shown

Title
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation Jialin Chen Yuelin Wang Cristian Bodnar Rex Ying Pietro Lió Yu Guang Wang 22 10 0 09 Nov 2023
Frameless Graph Knowledge Distillation Dai Shi Zhiqi Shao Yi Guo Junbin Gao 21 4 0 13 Jul 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 22 1 0 25 May 2023
SStaGCN: Simplified stacking based graph convolutional networks Jia Cai Zhilong Xiong Shaogao Lv GNN 30 1 0 16 Nov 2021
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks Cristian Bodnar Fabrizio Frasca Yu Guang Wang N. Otter Guido Montúfar Pietro Lió M. Bronstein 23 244 0 04 Mar 2021
SPAGAN: Shortest Path Graph Attention Network Yiding Yang Xinchao Wang Mingli Song Junsong Yuan Dacheng Tao GNN 130 94 0 10 Jan 2021
Decimated Framelet System on Graphs and Fast G-Framelet Transforms Xuebin Zheng Bingxin Zhou Yu Guang Wang Xiaosheng Zhuang 19 34 0 12 Dec 2020
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,801 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 231 3,202 0 24 Nov 2016