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"

42 / 92 papers shown

Title
Revisiting Random Walks for Learning on Graphs Jinwoo Kim Olga Zaghen Ayhan Suleymanzade Youngmin Ryou Seunghoon Hong 38 0 0 01 Jul 2024
KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning Roman Bresson Giannis Nikolentzos G. Panagopoulos Michail Chatzianastasis Jun Pang Michalis Vazirgiannis 46 42 0 26 Jun 2024
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark Yili Wang Yixin Liu Xu Shen Chenyu Li Kaize Ding Rui Miao Ying Wang Shirui Pan Xin Wang 16 6 0 21 Jun 2024
Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers Harald Semmelrock Tony Ross-Hellauer Simone Kopeinik Dieter Theiler Armin Haberl Stefan Thalmann Dominik Kowald 37 5 0 20 Jun 2024
RobGC: Towards Robust Graph Condensation Xinyi Gao Hongzhi Yin Tong Chen Guanhua Ye Wentao Zhang Bin Cui AAML 43 3 0 19 Jun 2024
GENIE: Watermarking Graph Neural Networks for Link Prediction Venkata Sai Pranav Bachina Ankit Gangwal Aaryan Ajay Sharma Charu Sharma 30 1 0 07 Jun 2024
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 21 6 0 22 May 2024
I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey Noah Lewis J. L. Bez Suren Byna 35 0 0 16 Apr 2024
Contextualized Messages Boost Graph Representations Brian Godwin Lim Galvin Brice Lim Renzo Roel Tan Kazushi Ikeda AI4CE 31 1 0 19 Mar 2024
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification Yutong Xia Runpeng Yu Yuxuan Liang Xavier Bresson Xinchao Wang Roger Zimmermann 25 4 0 18 Jan 2024
Disentangled Condensation for Large-scale Graphs Zhenbang Xiao Shunyu Liu Yu Wang Tongya Zheng Mingli Song Mingli Song Tongya Zheng DD 64 6 0 18 Jan 2024
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 21 1 0 29 Nov 2023
Supercharging Graph Transformers with Advective Diffusion Qitian Wu Chenxiao Yang Kaipeng Zeng Fan Nie AI4CE 28 6 0 10 Oct 2023
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning Jing Zhu Xiang Song V. Ioannidis Danai Koutra Christos Faloutsos 24 13 0 25 Sep 2023
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining Shengchao Liu Weitao Du Zhiming Ma Hongyu Guo Jian Tang 14 29 0 28 May 2023
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint Paiheng Xu Yuhang Zhou Bang An Wei Ai Furong Huang 12 6 0 25 May 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures Max Klabunde Tobias Schumacher M. Strohmaier Florian Lemmerich 43 63 0 10 May 2023
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs Matthieu Cordonnier Nicolas Keriven Nicolas M Tremblay Samuel Vaiter GNN 35 7 0 21 Apr 2023
Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification Zhen Tan Song Wang Kaize Ding Jundong Li Huan Liu 16 25 0 11 Dec 2022
A Gaze into the Internal Logic of Graph Neural Networks, with Logic Paul Tarau NAI 6 2 0 05 Aug 2022
Unified 2D and 3D Pre-Training of Molecular Representations Jinhua Zhu Yingce Xia Lijun Wu Shufang Xie Tao Qin Wen-gang Zhou Houqiang Li Tie-Yan Liu AI4CE 38 67 0 14 Jul 2022
Condensing Graphs via One-Step Gradient Matching Wei Jin Xianfeng Tang Haoming Jiang Zheng Li Danqing Zhang Jiliang Tang Bin Ying DD 11 98 0 15 Jun 2022
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization Quanqi Hu Yongjian Zhong Tianbao Yang 17 16 0 01 Jun 2022
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou Gitta Kutyniok Bruno Ribeiro OODD AI4CE 62 37 0 30 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 34 98 0 16 May 2022
Representing Long-Range Context for Graph Neural Networks with Global Attention Zhanghao Wu Paras Jain Matthew A. Wright Azalia Mirhoseini Joseph E. Gonzalez Ion Stoica GNN 16 258 0 21 Jan 2022
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design Sung Une Lee Boming Xia Yongan Zhang Ang Li Yingyan Lin GNN 34 45 0 22 Dec 2021
BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing Tianfeng Liu Yangrui Chen Dan Li Chuan Wu Yibo Zhu Jun He Yanghua Peng Hongzheng Chen Hongzhi Chen Chuanxiong Guo GNN 18 69 0 16 Dec 2021
Serpens: A High Bandwidth Memory Based Accelerator for General-Purpose Sparse Matrix-Vector Multiplication Linghao Song Yuze Chi Licheng Guo Jason Cong 9 40 0 24 Nov 2021
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 77 48 0 10 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 22 49 0 08 Nov 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 56 51 0 16 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 117 78 0 01 Oct 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 25 104 0 08 Mar 2021
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning Yixin Liu Zhao Li Shirui Pan Chen Gong Chuan Zhou George Karypis 7 277 0 27 Feb 2021
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development Kexin Huang Tianfan Fu Wenhao Gao Yue Zhao Yusuf Roohani J. Leskovec Connor W. Coley Cao Xiao Jimeng Sun Marinka Zitnik OOD LM&MA 8 258 0 18 Feb 2021
Heterogeneous Graph Transformer Ziniu Hu Yuxiao Dong Kuansan Wang Yizhou Sun 167 1,157 0 03 Mar 2020
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks Minjie Wang Da Zheng Zihao Ye Quan Gan Mufei Li ... J. Zhao Haotong Zhang Alex Smola Jinyang Li Zheng-Wei Zhang AI4CE GNN 177 665 0 03 Sep 2019
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 217 1,726 0 09 Jun 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,003 0 20 Apr 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 152 1,748 0 02 Mar 2017
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 228 3,202 0 24 Nov 2016