Graph-Coupled Oscillator Networks

4 February 2022

Papers citing "Graph-Coupled Oscillator Networks"

21 / 71 papers shown

Title
Node Embedding from Hamiltonian Information Propagation in Graph Neural Networks Qiyu Kang Kai Zhao Yang Song Sijie Wang Rui She Wee Peng Tay 22 0 0 02 Mar 2023
G-Signatures: Global Graph Propagation With Randomized Signatures Bernhard Schafl Lukas Gruber Johannes Brandstetter Sepp Hochreiter 12 2 0 17 Feb 2023
Temporal Graph Neural Networks for Irregular Data Joel Oskarsson Per Sidén Fredrik Lindsten AI4TS 11 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 31 108 0 06 Feb 2023
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification Moshe Eliasof E. Haber Eran Treister GNN 22 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 13 61 0 28 Nov 2022
GREAD: Graph Neural Reaction-Diffusion Networks Jeongwhan Choi Seoyoung Hong Noseong Park Sung-Bae Cho DiffM GNN 16 26 0 25 Nov 2022
Improving Graph Neural Networks with Learnable Propagation Operators Moshe Eliasof Lars Ruthotto Eran Treister 23 19 0 31 Oct 2022
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks Alessio Gravina D. Bacciu Claudio Gallicchio GNN 6 50 0 18 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 70 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 74 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 21 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 42 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 8 34 0 11 Jun 2022
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem Guanyu Cui Zhewei Wei 10 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 13 13 0 22 Dec 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 166 1,095 0 27 Apr 2021
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 181 907 0 02 Mar 2020
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 1,935 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 234 1,801 0 25 Nov 2016