Graph-Coupled Oscillator Networks

4 February 2022

Papers citing "Graph-Coupled Oscillator Networks"

23 / 73 papers shown

Title
Distributional Signals for Node Classification in Graph Neural Networks Feng Ji See Hian Lee Kai Zhao Wee Peng Tay Jielong Yang 13 2 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
Node Embedding from Hamiltonian Information Propagation in Graph Neural Networks Qiyu Kang Kai Zhao Yang Song Sijie Wang Rui She Wee Peng Tay 38 0 0 02 Mar 2023
G-Signatures: Global Graph Propagation With Randomized Signatures Bernhard Schafl Lukas Gruber Johannes Brandstetter Sepp Hochreiter 22 2 0 17 Feb 2023
Temporal Graph Neural Networks for Irregular Data Joel Oskarsson Per Sidén Fredrik Lindsten AI4TS 23 11 0 16 Feb 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology Francesco Di Giovanni Lorenzo Giusti Federico Barbero Giulia Luise Pietro Lio Michael M. Bronstein 48 112 0 06 Feb 2023
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification Moshe Eliasof E. Haber Eran Treister GNN 30 0 0 29 Nov 2022
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature K. Nguyen Hieu Nong T. Nguyen Nhat Ho Khuong N. Nguyen Vinh Phu Nguyen 27 63 0 28 Nov 2022
GREAD: Graph Neural Reaction-Diffusion Networks Jeongwhan Choi Seoyoung Hong Noseong Park Sung-Bae Cho DiffM GNN 21 27 0 25 Nov 2022
Improving Graph Neural Networks with Learnable Propagation Operators Moshe Eliasof Lars Ruthotto Eran Treister 34 20 0 31 Oct 2022
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks Alessio Gravina D. Bacciu Claudio Gallicchio GNN 21 50 0 18 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 75 13 0 08 Oct 2022
Gradient Gating for Deep Multi-Rate Learning on Graphs T. Konstantin Rusch B. Chamberlain Michael W. Mahoney Michael M. Bronstein Siddhartha Mishra 79 53 0 02 Oct 2022
Structural Inference of Networked Dynamical Systems with Universal Differential Equations James Koch Zhao Chen Aaron Tuor Ján Drgoňa D. Vrabie PINN 31 10 0 11 Jul 2022
Understanding convolution on graphs via energies Francesco Di Giovanni J. Rowbottom B. Chamberlain Thomas Markovich Michael M. Bronstein GNN 18 45 0 22 Jun 2022
ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition Yuelin Wang Kai Yi Xinliang Liu Yu Guang Wang Shi Jin 18 33 0 11 Jun 2022
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem Guanyu Cui Zhewei Wei 27 7 0 31 Jan 2022
SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks Weigang Lu Yibing Zhan Binbin Lin Ziyu Guan Liu Liu Baosheng Yu Wei Zhao Yaming Yang Dacheng Tao GNN 21 13 0 22 Dec 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 176 1,111 0 27 Apr 2021
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 917 0 02 Mar 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,080 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 276 1,944 0 09 Jun 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016