Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training

24 December 2023

Papers citing "Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training"

6 / 6 papers shown

Title
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition Xin Gao Tong Chen Wentao Zhang Junliang Yu Guanhua Ye Quoc Viet Hung Nguyen 71 7 0 22 May 2024
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation Jiong Zhu Aishwarya N. Reganti E-Wen Huang Charles Dickens Nikhil S. Rao Karthik Subbian Danai Koutra GNN FedML 53 3 0 17 May 2023
Condensing Graphs via One-Step Gradient Matching Wei Jin Xianfeng Tang Haoming Jiang Zheng Li Danqing Zhang Jiliang Tang Bin Ying DD 47 107 0 15 Jun 2022
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 131 2,687 0 02 May 2020
Network Embedding: on Compression and Learning Esra Akbas M. E. Aktas GNN 21 9 0 05 Jul 2019
Spectral Networks and Locally Connected Networks on Graphs Joan Bruna Wojciech Zaremba Arthur Szlam Yann LeCun GNN 28 4,856 0 21 Dec 2013