Open Graph Benchmark: Datasets for Machine Learning on Graphs

2 May 2020

Yuxiao Dong

Papers citing "Open Graph Benchmark: Datasets for Machine Learning on Graphs"

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Title
Serpens: A High Bandwidth Memory Based Accelerator for General-Purpose Sparse Matrix-Vector Multiplication Linghao Song Yuze Chi Licheng Guo Jason Cong 24 40 0 24 Nov 2021
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features Emanuele Rossi Henry Kenlay Maria I. Gorinova B. Chamberlain Xiaowen Dong M. Bronstein 43 88 0 23 Nov 2021
Node-Level Differentially Private Graph Neural Networks Ameya Daigavane Gagan Madan Aditya Sinha Abhradeep Thakurta Gaurav Aggarwal Prateek Jain 38 55 0 23 Nov 2021
Network In Graph Neural Network Xiang Song Runjie Ma Jiahang Li Muhan Zhang David Wipf GNN 24 10 0 23 Nov 2021
Graph Neural Networks with Parallel Neighborhood Aggregations for Graph Classification Siddhant Doshi S. Chepuri GNN 28 4 0 22 Nov 2021
Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming Yizhen Zheng Ming Jin Shirui Pan Yuan-Fang Li Hao Peng Ming Li Zhao‐Rui Li SSL 38 24 0 20 Nov 2021
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs Shaohua Fan Xiao Wang Chuan Shi Peng Cui Bai Wang CML OOD OODD AI4CE 70 81 0 20 Nov 2021
Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs G. Edwards Sebastian Nilsson Benedek Rozemberczki Eliseo Papa 23 12 0 20 Nov 2021
QGTC: Accelerating Quantized Graph Neural Networks via GPU Tensor Core Yuke Wang Boyuan Feng Yufei Ding GNN 33 41 0 18 Nov 2021
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks M. Ramezani Weilin Cong Mehrdad Mahdavi M. Kandemir A. Sivasubramaniam GNN 28 32 0 16 Nov 2021
$p$ -Laplacian Based Graph Neural Networks Guoji Fu P. Zhao Yatao Bian 25 45 0 14 Nov 2021
Implicit vs Unfolded Graph Neural Networks Yongyi Yang Tang Liu Yangkun Wang Zengfeng Huang David Wipf 54 15 0 12 Nov 2021
Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs Hesham Mostafa GNN 51 21 0 11 Nov 2021
Implicit SVD for Graph Representation Learning Sami Abu-El-Haija Hesham Mostafa Marcel Nassar V. Crespi Greg Ver Steeg Aram Galstyan 45 5 0 11 Nov 2021
Graph Neural Network Training with Data Tiering S. Min Kun Wu Mert Hidayetoğlu Jinjun Xiong Xiang Song Wen-mei W. Hwu GNN 29 15 0 10 Nov 2021
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 79 49 0 10 Nov 2021
On Representation Knowledge Distillation for Graph Neural Networks Chaitanya K. Joshi Fayao Liu Xu Xun Jie Lin Chuan-Sheng Foo 27 54 0 09 Nov 2021
MassFormer: Tandem Mass Spectrum Prediction for Small Molecules using Graph Transformers A. Young Bo Wang Hannes L. Röst 29 5 0 08 Nov 2021
Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Klicpera Chandan Yeshwanth Stephan Günnemann 42 35 0 08 Nov 2021
Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning Qinkai Zheng Xu Zou Yuxiao Dong Yukuo Cen Da Yin Jiarong Xu Yang Yang Jie Tang OOD AAML 30 50 0 08 Nov 2021
GNNear: Accelerating Full-Batch Training of Graph Neural Networks with Near-Memory Processing Zhe Zhou Cong Li Xuechao Wei Xiaoyang Wang Guangyu Sun GNN 22 24 0 01 Nov 2021
Optimizing Sparse Matrix Multiplications for Graph Neural Networks Shenghao Qiu You Liang Zheng Wang GNN 31 18 0 30 Oct 2021
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction Eli Chien Wei-Cheng Chang Cho-Jui Hsieh Hsiang-Fu Yu Jiong Zhang O. Milenkovic Inderjit S Dhillon 156 133 0 29 Oct 2021
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 32 74 0 28 Oct 2021
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs Hongyu Ren H. Dai Bo Dai Xinyun Chen Denny Zhou J. Leskovec Dale Schuurmans LRM 15 41 0 28 Oct 2021
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks Hao Xue Kaixiong Zhou Tianlong Chen Kai Guo Xia Hu Yi Chang Xin Wang AAML 32 15 0 28 Oct 2021
RIM: Reliable Influence-based Active Learning on Graphs Wentao Zhang Yexin Wang Zhenbang You Mengyao Cao Ping Huang Jiulong Shan Zhi-Xin Yang Bin Cui 40 30 0 28 Oct 2021
Towards a Taxonomy of Graph Learning Datasets Renming Liu Semih Cantürk Frederik Wenkel Dylan Sandfelder Devin Kreuzer ... Michal Perlmutter Bastian Rieck M. Hirn Guy Wolf Ladislav Rampášek 19 0 0 27 Oct 2021
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Derek Lim Felix Hohne Xiuyu Li Sijia Huang Vaishnavi Gupta Omkar Bhalerao Ser-Nam Lim 61 340 0 27 Oct 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization Mucong Ding Kezhi Kong Jingling Li Chen Zhu John P. Dickerson Furong Huang Tom Goldstein GNN MQ 33 47 0 27 Oct 2021
Robustness of Graph Neural Networks at Scale Simon Geisler Tobias Schmidt Hakan cSirin Daniel Zügner Aleksandar Bojchevski Stephan Günnemann AAML 30 126 0 26 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 46 81 0 26 Oct 2021
Heterogeneous Temporal Graph Neural Network Yujie Fan Mingxuan Ju Chuxu Zhang Liang Zhao Yanfang Ye 24 36 0 26 Oct 2021
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features Jiuhai Chen Jonas W. Mueller V. Ioannidis Soji Adeshina Yangkun Wang Tom Goldstein David Wipf 40 12 0 26 Oct 2021
Nested Graph Neural Networks Muhan Zhang Pan Li 27 165 0 25 Oct 2021
SEA: Graph Shell Attention in Graph Neural Networks Christian Frey Yunpu Ma Matthias Schubert 39 1 0 20 Oct 2021
Steganography of Complex Networks Daewon Lee 17 1 0 20 Oct 2021
What is Learned in Knowledge Graph Embeddings? Michael R Douglas Michael Simkin Omri Ben-Eliezer Tianqi Wu Peter Chin Trung D. Q. Dang Andrew Wood 22 1 0 19 Oct 2021
Beltrami Flow and Neural Diffusion on Graphs B. Chamberlain J. Rowbottom D. Eynard Francesco Di Giovanni Xiaowen Dong M. Bronstein AI4CE 34 80 0 18 Oct 2021
ifMixup: Interpolating Graph Pair to Regularize Graph Classification Hongyu Guo Yongyi Mao 32 9 0 18 Oct 2021
Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation Shichang Zhang Yozen Liu Yizhou Sun Neil Shah 38 174 0 17 Oct 2021
MG-GCN: Scalable Multi-GPU GCN Training Framework M. F. Balin Kaan Sancak Ümit V. Çatalyürek GNN 39 7 0 17 Oct 2021
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining Tim Kaler Nickolas Stathas Anne Ouyang A. Iliopoulos Tao B. Schardl C. E. Leiserson Jie Chen GNN 70 53 0 16 Oct 2021
Graph Neural Networks with Learnable Structural and Positional Representations Vijay Prakash Dwivedi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson GNN 197 315 0 15 Oct 2021
Graph Condensation for Graph Neural Networks Wei Jin Lingxiao Zhao Shichang Zhang Yozen Liu Jiliang Tang Neil Shah DD AI4CE 37 148 0 14 Oct 2021
Why Propagate Alone? Parallel Use of Labels and Features on Graphs Yangkun Wang Jiarui Jin Weinan Zhang Yongyi Yang Jiuhai Chen Quan Gan Yong Yu Zheng-Wei Zhang Zengfeng Huang David Wipf AAML 58 12 0 14 Oct 2021
SoGCN: Second-Order Graph Convolutional Networks Peihao Wang Yuehao Wang Hua Lin Jianbo Shi 37 3 0 14 Oct 2021
Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation Cole Hawkins V. Ioannidis Soji Adeshina George Karypis GNN SSL 31 2 0 12 Oct 2021
GRAPE for Fast and Scalable Graph Processing and random walk-based Embedding L. Cappelletti Tommaso Fontana E. Casiraghi V. Ravanmehr Tiffany J. Callahan ... marcin p. joachimiak Christopher J. Mungall Peter N. Robinson Justin P Reese Giorgio Valentini 31 24 0 12 Oct 2021
Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking Platform Zhen Xu Sergio Escalera Isabelle M Guyon Adrien Pavao M. Richard Wei-Wei Tu Quanming Yao Huan Zhao 106 49 0 12 Oct 2021