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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"

50 / 1,644 papers shown

Title
CIN++: Enhancing Topological Message Passing Lorenzo Giusti Teodora Reu Francesco Ceccarelli Cristian Bodnar Pietro Lio GNN 108 10 0 06 Jun 2023
Explaining and Adapting Graph Conditional Shift Qi Zhu Yizhu Jiao Natalia Ponomareva Jiawei Han Bryan Perozzi OOD 75 10 0 05 Jun 2023
Structural Re-weighting Improves Graph Domain Adaptation Shikun Liu Tianchun Li Yongbin Feng Nhan Tran Haiying Zhao Qiu Qiang Pan Li OOD AI4CE 81 39 0 05 Jun 2023
LibAUC: A Deep Learning Library for X-Risk Optimization Zhuoning Yuan Dixian Zhu Zimeng Qiu Gang Li Xuanhui Wang Tianbao Yang BDL 118 16 0 05 Jun 2023
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data Xin Zheng Miao Zhang C. Chen Quoc Viet Hung Nguyen Xingquan Zhu Shirui Pan DD 120 69 0 05 Jun 2023
Adaptive Message Quantization and Parallelization for Distributed Full-graph GNN Training Borui Wan Juntao Zhao Chuan Wu GNN 56 15 0 02 Jun 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? Haitao Mao Zhikai Chen Wei Jin Haoyu Han Yao Ma Tong Zhao Neil Shah Jiliang Tang 118 36 0 02 Jun 2023
EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost Jaeseung Heo Seungbeom Lee SungSoo Ahn Dongwoo Kim 70 1 0 02 Jun 2023
Improving Energy Conserving Descent for Machine Learning: Theory and Practice G. Luca Alice Gatti E. Silverstein 71 1 0 01 Jun 2023
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization Kaixuan Chen Shunyu Liu Tongtian Zhu Tongya Zheng Haofei Zhang Zunlei Feng Jingwen Ye Mingli Song 135 16 0 31 May 2023
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials Mingguo He Zhewei Wei Shi Feng Zhengjie Huang Weibin Li Yu Sun Dianhai Yu 79 10 0 31 May 2023
Bures-Wasserstein Means of Graphs Isabel Haasler P. Frossard 48 3 0 31 May 2023
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning Xiaoxin He Xavier Bresson T. Laurent Adam Perold Yann LeCun Bryan Hooi 140 86 0 31 May 2023
Graph Entropy Minimization for Semi-supervised Node Classification Yi Luo Guangchun Luo Ke Qin Aiguo Chen 68 0 0 31 May 2023
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks Jintang Li Huizhe Zhang Ruofan Wu Zulun Zhu Baokun Wang Changhua Meng Zibin Zheng Liang Chen SSL 68 9 0 30 May 2023
Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks Qiyu Kang Kai Zhao Yang Song Sijie Wang Wee Peng Tay 70 12 0 30 May 2023
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks Yuwen Li Miao Xiong Bryan Hooi 78 7 0 30 May 2023
Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection Hezhe Qiao Guansong Pang 139 30 0 29 May 2023
Learning Strong Graph Neural Networks with Weak Information Yixin Liu Kaize Ding Jianling Wang V. Lee Huan Liu Shirui Pan 81 46 0 29 May 2023
Dink-Net: Neural Clustering on Large Graphs Yue Liu K. Liang Jun Xia Sihang Zhou Xihong Yang Xinwang Liu Stan Z. Li GNN 158 55 0 28 May 2023
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining Shengchao Liu Weitao Du Zhiming Ma Hongyu Guo Jian Tang 107 33 0 28 May 2023
AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs Yangjie Zhou Yaoxu Song Jingwen Leng Zihan Liu Weihao Cui Zhendong Zhang Cong Guo Quan Chen Li-Wei Li Minyi Guo GNN 77 2 0 27 May 2023
Confidence-Based Feature Imputation for Graphs with Partially Known Features Daeho Um Jiwoong Park Seulki Park Hawook Jeong DiffM 75 17 0 26 May 2023
Unsupervised Embedding Quality Evaluation Anton Tsitsulin Marina Munkhoeva Bryan Perozzi SSL 91 7 0 26 May 2023
Fast Online Node Labeling for Very Large Graphs Baojian Zhou Yifan Sun Reza Babanezhad 49 4 0 25 May 2023
How to Turn Your Knowledge Graph Embeddings into Generative Models Lorenzo Loconte Nicola Di Mauro Robert Peharz Antonio Vergari 83 16 0 25 May 2023
Towards Label Position Bias in Graph Neural Networks Haoyu Han Xiaorui Liu Feng Shi MohamadAli Torkamani Charu C. Aggarwal Jiliang Tang 97 4 0 25 May 2023
Union Subgraph Neural Networks Jiaxing Xu Aihu Zhang Qingtian Bian Vijay Prakash Dwivedi Yiping Ke GNN 90 7 0 25 May 2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization Kha-Dinh Luong Mert Kosan A. Silva Ambuj K. Singh 88 6 0 25 May 2023
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint Paiheng Xu Yuhang Zhou Bang An Wei Ai Furong Huang 138 6 0 25 May 2023
Size Generalization of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective Gao Li Danai Koutra Yujun Yan 31 1 0 24 May 2023
Editable Graph Neural Network for Node Classifications Zirui Liu Zhimeng Jiang Shaochen Zhong Kaixiong Zhou Li Li Rui Chen Soo-Hyun Choi Helen Zhou 79 6 0 24 May 2023
GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking Jiayan Guo Lun Du Hengyu Liu Mengyu Zhou Xinyi He Shi Han AI4MH 96 167 0 24 May 2023
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding Nicolas Keriven Samuel Vaiter 77 12 0 24 May 2023
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks Peng Xu Lin Zhang Xuanzhou Liu Jiaqi Sun Yue Zhao Haiqing Yang Bei Yu GNN 78 9 0 23 May 2023
On Structural Expressive Power of Graph Transformers Wenhao Zhu Tianyu Wen Guojie Song Liangji Wang Bo Zheng 72 15 0 23 May 2023
The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey Jana Vatter R. Mayer Hans-Arno Jacobsen GNN AI4TS AI4CE 96 29 0 23 May 2023
Link Prediction without Graph Neural Networks Zexi Huang Mert Kosan A. Silva Ambuj K. Singh 112 3 0 23 May 2023
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention Hongjun Wang Jiyuan Chen Lun Du Qiang Fu Shi Han Xuan Song CML GNN 83 5 0 22 May 2023
PRODIGY: Enabling In-context Learning Over Graphs Qian Huang Hongyu Ren Peng Chen Gregor Krvzmanc D. Zeng Percy Liang J. Leskovec 122 77 0 21 May 2023
Self-Explainable Graph Neural Networks for Link Prediction Huaisheng Zhu Dongsheng Luo Xianfeng Tang Junjie Xu Hui Liu Suhang Wang 64 1 0 21 May 2023
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation Eli Chien Jiong Zhang Cho-Jui Hsieh Jyun-Yu Jiang Wei-Cheng Chang O. Milenkovic Hsiang-Fu Yu 86 10 0 21 May 2023
Learning Large Graph Property Prediction via Graph Segment Training Kaidi Cao P. Phothilimthana Sami Abu-El-Haija Dustin Zelle Yanqi Zhou Charith Mendis J. Leskovec Bryan Perozzi 98 9 0 21 May 2023
PTGB: Pre-Train Graph Neural Networks for Brain Network Analysis Yi Yang Hejie Cui Carl Yang 91 19 0 20 May 2023
Graph Propagation Transformer for Graph Representation Learning Zhe Chen Hao Hao Tan Tao Wang Tianrun Shen Tong Lu Qiuying Peng Cheng Cheng Yue Qi 82 13 0 19 May 2023
Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness Zeyuan Tan Xiulong Yuan Congjie He Man-Kit Sit Guo Li Xiaoze Liu Baole Ai Kai Zeng Peter R. Pietzuch Kai Zou GNN 56 17 0 18 May 2023
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph Chenguang Du Kaichun Yao Hengshu Zhu Deqing Wang Fuzhen Zhuang Hui Xiong 69 6 0 18 May 2023
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks Federico Errica Mathias Niepert TPM 97 5 0 17 May 2023
Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi Bertrand Charpentier Francesco Di Giovanni Fabrizio Frasca Stephan Günnemann Michael M. Bronstein 131 71 0 17 May 2023
G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks Anchun Gui Jinqiang Ye Han Xiao 80 22 0 17 May 2023