Scaling Up Graph Neural Networks Via Graph Coarsening

9 June 2021

Papers citing "Scaling Up Graph Neural Networks Via Graph Coarsening"

36 / 36 papers shown

Title
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening Guoming Li Jian Yang Yifan Chen 181 0 0 20 May 2025
FIT-GNN: Faster Inference Time for GNNs Using Coarsening Shubhajit Roy Hrriday Ruparel Kishan Ved Anirban Dasgupta GNN AI4CE 157 0 0 28 Jan 2025
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 132 8 0 22 May 2024
Interpreting and Unifying Graph Neural Networks with An Optimization Framework Meiqi Zhu Xiao Wang C. Shi Houye Ji Peng Cui AI4CE 111 203 0 28 Jan 2021
Scalable Graph Neural Networks via Bidirectional Propagation Ming Chen Zhewei Wei Bolin Ding Yaliang Li Ye Yuan Xiaoyong Du Ji-Rong Wen GNN 50 145 0 29 Oct 2020
Learning Mesh-Based Simulation with Graph Networks Tobias Pfaff Meire Fortunato Alvaro Sanchez-Gonzalez Peter W. Battaglia AI4CE 82 803 0 07 Oct 2020
Towards Deeper Graph Neural Networks Meng Liu Hongyang Gao Shuiwang Ji GNN AI4CE 103 607 0 18 Jul 2020
Faster Graph Embeddings via Coarsening Matthew Fahrbach Gramoz Goranci Richard Peng Sushant Sachdeva Chi Wang 51 28 0 06 Jul 2020
Simple and Deep Graph Convolutional Networks Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding Yaliang Li GNN 124 1,494 0 04 Jul 2020
Scaling Graph Neural Networks with Approximate PageRank Aleksandar Bojchevski Johannes Klicpera Bryan Perozzi Amol Kapoor Martin J. Blais Benedek Rozemberczki Michal Lukasik Stephan Günnemann GNN 157 373 0 03 Jul 2020
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks Weilin Cong R. Forsati M. Kandemir M. Mahdavi 85 87 0 24 Jun 2020
LambdaNet: Probabilistic Type Inference using Graph Neural Networks Jiayi Wei Maruth Goyal Greg Durrett Işıl Dillig 103 108 0 29 Apr 2020
SIGN: Scalable Inception Graph Neural Networks Fabrizio Frasca Emanuele Rossi D. Eynard B. Chamberlain M. Bronstein Federico Monti GNN 129 399 0 23 Apr 2020
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks Difan Zou Ziniu Hu Yewen Wang Song Jiang Yizhou Sun Quanquan Gu GNN 95 283 0 17 Nov 2019
GraphZoom: A multi-level spectral approach for accurate and scalable graph embedding Chenhui Deng Zhiqiang Zhao Yongyu Wang Zhiru Zhang Zhuo Feng 66 106 0 06 Oct 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 110 1,343 0 25 Jul 2019
GraphSAINT: Graph Sampling Based Inductive Learning Method Hanqing Zeng Hongkuan Zhou Ajitesh Srivastava Rajgopal Kannan Viktor Prasanna GNN 137 968 0 10 Jul 2019
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks Wei-Lin Chiang Xuanqing Liu Si Si Yang Li Samy Bengio Cho-Jui Hsieh GNN 147 1,275 0 20 May 2019
Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs Aditya Sanjay Paliwal Felix Gimeno Vinod Nair Yujia Li Miles Lubin Pushmeet Kohli Oriol Vinyals OffRL GNN 70 67 0 07 May 2019
Inductive Matrix Completion Based on Graph Neural Networks Muhan Zhang Yixin Chen 80 237 0 26 Apr 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 234 4,361 0 06 Mar 2019
Simplifying Graph Convolutional Networks Felix Wu Tianyi Zhang Amauri Souza Christopher Fifty Tao Yu Kilian Q. Weinberger GNN 244 3,179 0 19 Feb 2019
Pitfalls of Graph Neural Network Evaluation Oleksandr Shchur Maximilian Mumme Aleksandar Bojchevski Stephan Günnemann GNN 168 1,364 0 14 Nov 2018
Predict then Propagate: Graph Neural Networks meet Personalized PageRank Johannes Klicpera Aleksandar Bojchevski Stephan Günnemann GNN 222 1,691 0 14 Oct 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 245 7,681 0 01 Oct 2018
Graph Convolutional Neural Networks for Web-Scale Recommender Systems Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William L. Hamilton J. Leskovec GNN BDL 266 3,549 0 06 Jun 2018
MILE: A Multi-Level Framework for Scalable Graph Embedding Jiongqian Liang Saket Gurukar Srinivas Parthasarathy GNN 57 78 0 26 Feb 2018
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling Jie Chen Tengfei Ma Cao Xiao GNN 146 1,516 0 30 Jan 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 479 20,225 0 30 Oct 2017
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking Aleksandar Bojchevski Stephan Günnemann BDL 85 647 0 12 Jul 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 509 15,300 0 07 Jun 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 415 1,824 0 25 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 650 29,154 0 09 Sep 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 356 7,669 0 30 Jun 2016
Revisiting Semi-Supervised Learning with Graph Embeddings Zhilin Yang William W. Cohen Ruslan Salakhutdinov GNN SSL 171 2,103 0 29 Mar 2016
Spectral Networks and Locally Connected Networks on Graphs Joan Bruna Wojciech Zaremba Arthur Szlam Yann LeCun GNN 225 4,884 0 21 Dec 2013