From Node Interaction to Hop Interaction: New Effective and Scalable
Graph Learning Paradigm

From Node Interaction to Hop Interaction: New Effective and Scalable Graph Learning Paradigm

21 November 2022

Jie Chen

Papers citing "From Node Interaction to Hop Interaction: New Effective and Scalable Graph Learning Paradigm"

8 / 8 papers shown

Title
GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers Guoguo Ai Guansong Pang Hezhe Qiao Yuan Gao Hui Yan 67 0 0 26 Nov 2024
Graph Neural Networks for Graphs with Heterophily: A Survey Xin-Yang Zheng Yi Wang Yixin Liu Ming Li Miao Zhang Di Jin Philip S. Yu Shirui Pan 19 213 0 14 Feb 2022
Memory-based Message Passing: Decoupling the Message for Propogation from Discrimination Jie Chen Weiqi Liu Jianghuai Pu 12 10 0 01 Feb 2022
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning Yifan Zhang Bryan Hooi Dapeng Hu Jian Liang Jiashi Feng 71 64 0 12 Feb 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 87 554 0 04 Jan 2021
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud Weijing Shi Ragunathan R. Rajkumar 3DPC 139 731 0 02 Mar 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,072 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 229 1,935 0 09 Jun 2018