Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks

4 March 2021

Papers citing "Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks"

9 / 159 papers shown

Title
Topological Graph Neural Networks Max Horn E. Brouwer Michael Moor Yves Moreau Bastian Alexander Rieck Karsten M. Borgwardt AI4CE 25 90 0 15 Feb 2021
How Framelets Enhance Graph Neural Networks Xuebin Zheng Bingxin Zhou Junbin Gao Yu Guang Wang Pietro Lió Ming Li Guido Montúfar 56 69 0 13 Feb 2021
Signal Processing on Higher-Order Networks: Livin' on the Edge ... and Beyond Michael T. Schaub Yu Zhu Jean-Baptiste Seby T. Roddenberry Santiago Segarra 126 145 0 14 Jan 2021
Decimated Framelet System on Graphs and Fast G-Framelet Transforms Xuebin Zheng Bingxin Zhou Yu Guang Wang Xiaosheng Zhuang 40 35 0 12 Dec 2020
DiffusionNet: Discretization Agnostic Learning on Surfaces Nicholas Sharp Souhaib Attaiki Keenan Crane M. Ovsjanikov 3DH 16 196 0 01 Dec 2020
Deep Graph Mapper: Seeing Graphs through the Neural Lens Cristian Bodnar Cătălina Cangea Pietro Lió 23 42 0 10 Feb 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,944 0 09 Jun 2018
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 259 3,239 0 24 Nov 2016
Benefits of depth in neural networks Matus Telgarsky 148 602 0 14 Feb 2016