v1v2v3v4v5v6v7 (latest)

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
Graph Positional and Structural Encoder Semih Cantürk Renming Liu Olivier Lapointe-Gagné Vincent Létourneau Guy Wolf Dominique Beaini Ladislav Rampášek 83 18 0 14 Jul 2023
Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test Arjun Subramonian Adina Williams Maximilian Nickel Yizhou Sun Levent Sagun 73 0 0 11 Jul 2023
Source-Aware Embedding Training on Heterogeneous Information Networks Tsai Hor Chan Chi Ho Wong Jiajun Shen Guosheng Yin 49 5 0 10 Jul 2023
Learning to Group Auxiliary Datasets for Molecule Ting Huang Ziniu Hu Rex Ying 61 0 0 08 Jul 2023
Rosko: Row Skipping Outer Products for Sparse Matrix Multiplication Kernels Vikas Natesh Andrew Sabot H. T. Kung Mark Ting 58 0 0 08 Jul 2023
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs Zhikai Chen Haitao Mao Hang Li Wei Jin Haifang Wen ... Shuaiqiang Wang D. Yin Wenqi Fan Hui Liu Jiliang Tang AI4CE 162 288 0 07 Jul 2023
PlanE: Representation Learning over Planar Graphs Radoslav Dimitrov Zeyang Zhao Ralph Abboud .Ismail .Ilkan Ceylan GNN 70 10 0 03 Jul 2023
Temporal Graph Benchmark for Machine Learning on Temporal Graphs Shenyang Huang Farimah Poursafaei Jacob Danovitch Matthias Fey Weihua Hu Emanuele Rossi J. Leskovec Michael M. Bronstein Guillaume Rabusseau Reihaneh Rabbany 103 98 0 03 Jul 2023
Shared Growth of Graph Neural Networks via Prompted Free-direction Knowledge Distillation Kaituo Feng Yikun Miao Changsheng Li Ye Yuan Guoren Wang 121 0 0 02 Jul 2023
InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs Dalong Zhang Xianzheng Song Zhiyang Hu Yang Li Miao Tao Binbin Hu Lin Wang Qing Cui Jun Zhou GNN 62 4 0 01 Jul 2023
Graphtester: Exploring Theoretical Boundaries of GNNs on Graph Datasets Eren Akbiyik Florian Grötschla Béni Egressy Roger Wattenhofer 41 2 0 30 Jun 2023
Diffusion-Jump GNNs: Homophiliation via Learnable Metric Filters Ahmed Begga Francisco Escolano M. Lozano Edwin R. Hancock 86 2 0 29 Jun 2023
Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses Jeongmin Brian Park Vikram Sharma Mailthody Zaid Qureshi Wen-mei W. Hwu GNN 83 14 0 28 Jun 2023
Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications Xinyu Ma Xu Chu Yasha Wang Yang Lin Junfeng Zhao Liantao Ma Wenwu Zhu 76 9 0 28 Jun 2023
Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization Ling Yang Jiayi Zheng Heyuan Wang Zhongyi Liu Zhilin Huang Shenda Hong Wentao Zhang Tengjiao Wang 100 16 0 28 Jun 2023
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions Lukas Gosch Simon Geisler Daniel Sturm Bertrand Charpentier Daniel Zügner Stephan Günnemann AAML GNN 101 32 0 27 Jun 2023
Unsupervised Episode Generation for Graph Meta-learning Jihyeong Jung Sang-gyu Seo Sungwon Kim Chanyoung Park BDL 82 0 0 27 Jun 2023
SENSEi: Input-Sensitive Compilation for Accelerating GNNs Damitha Sandeepa Lenadora Vimarsh Sathia Gerasimos Gerogiannis Serif Yesil Josep Torrellas Charith Mendis GNN 68 1 0 27 Jun 2023
Contrastive Meta-Learning for Few-shot Node Classification Song Wang Zhen Tan Huan Liu Jundong Li 67 17 0 27 Jun 2023
TransERR: Translation-based Knowledge Graph Embedding via Efficient Relation Rotation Jiang Li Xiangdong Su Fujun Zhang Guanglai Gao 92 1 0 26 Jun 2023
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware Shichang Zhang Atefeh Sohrabizadeh Cheng Wan Zijie Huang Ziniu Hu Yewen Wang Yingyan Lin Lin Jason Cong Yizhou Sun GNN AI4CE 103 25 0 24 Jun 2023
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities Dongyue Li Haotian Ju Aneesh Sharma Hongyang R. Zhang 147 8 0 24 Jun 2023
BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs Loc Hoang Rita Brugarolas Brufau Ke Ding Bo Wu GNN 61 2 0 23 Jun 2023
Directional diffusion models for graph representation learning Run Yang Yuling Yang Fan Zhou Qiang Sun DiffM 49 14 0 22 Jun 2023
On Exploring Node-feature and Graph-structure Diversities for Node Drop Graph Pooling Chuang Liu Yibing Zhan Baosheng Yu Liu Liu Bo Du Wenbin Hu Tongliang Liu 103 12 0 22 Jun 2023
Provably Powerful Graph Neural Networks for Directed Multigraphs Béni Egressy Luc von Niederhäusern Jovan Blanusa Erik Altman Roger Wattenhofer Kubilay Atasu 103 19 0 20 Jun 2023
P-tensors: a General Formalism for Constructing Higher Order Message Passing Networks Tianyi Sun Andrew R. Hands Risi Kondor 71 2 0 19 Jun 2023
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations Qitian Wu Wen-Long Zhao Chenxiao Yang Hengrui Zhang Fan Nie Haitian Jiang Yatao Bian Junchi Yan AI4CE 131 100 0 19 Jun 2023
CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification Le-le Cao Vilhelm von Ehrenheim Mark Granroth-Wilding Richard Anselmo Stahl Andrew McCornack Armin Catovic Dhiana Deva Cavalcanti Rocha 102 4 0 18 Jun 2023
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking Juanhui Li Harry Shomer Haitao Mao Shenglai Zeng Yao Ma Neil Shah Jiliang Tang D. Yin 174 59 0 18 Jun 2023
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning Zhiyao Zhou Sheng Zhou Bochao Mao Xu Zhou Jiawei Chen Qiaoyu Tan Daochen Zha Yan Feng Chun-Yen Chen C. Wang 141 24 0 17 Jun 2023
HomoGCL: Rethinking Homophily in Graph Contrastive Learning Wenzhong Li Changdong Wang Hui Xiong Jian-Huang Lai 84 25 0 16 Jun 2023
GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification Wenzhong Li Changdong Wang Hui Xiong Jian-Huang Lai 97 28 0 16 Jun 2023
The Split Matters: Flat Minima Methods for Improving the Performance of GNNs N. Lell A. Scherp 72 1 0 15 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 99 24 0 15 Jun 2023
Hyperbolic Convolution via Kernel Point Aggregation Eric Qu Dongmian Zou 87 3 0 15 Jun 2023
A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening Yifan Chen Rentian Yao Yun Yang Jie Chen 86 8 0 15 Jun 2023
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification Qitian Wu Wentao Zhao Zenan Li David Wipf Junchi Yan 68 231 0 14 Jun 2023
A Simple and Scalable Graph Neural Network for Large Directed Graphs Seiji Maekawa Yuya Sasaki Makoto Onizuka GNN 70 0 0 14 Jun 2023
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting Xu Liu Yutong Xia Yuxuan Liang Junfeng Hu Yiwei Wang Lei Bai Chaoqin Huang Zhenguang Liu Bryan Hooi Roger Zimmermann AI4TS 84 81 0 14 Jun 2023
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization Xiner Li Shurui Gui Youzhi Luo Shuiwang Ji OODD OOD 91 14 0 13 Jun 2023
Graph Mixup with Soft Alignments Hongyi Ling Zhimeng Jiang Meng Liu Shuiwang Ji Na Zou AAML 77 22 0 11 Jun 2023
D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching Xuanzhou Liu Lin Zhang Jiaqi Sun Yujiu Yang Haiqing Yang 61 2 0 10 Jun 2023
Virtual Node Tuning for Few-shot Node Classification Zhen Tan Ruocheng Guo Kaize Ding Huan Liu 98 43 0 09 Jun 2023
Path Neural Networks: Expressive and Accurate Graph Neural Networks Gaspard Michel Giannis Nikolentzos J. Lutzeyer Michalis Vazirgiannis GNN 95 31 0 09 Jun 2023
Expectation-Complete Graph Representations with Homomorphisms Pascal Welke Maximilian Thiessen Fabian Jogl Thomas Gärtner 55 9 0 09 Jun 2023
Efficient GNN Explanation via Learning Removal-based Attribution Yao Rong Guanchu Wang Qizhang Feng Ninghao Liu Zirui Liu Enkelejda Kasneci Helen Zhou 91 9 0 09 Jun 2023
Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs Lirong Wu Haitao Lin Yufei Huang Stan Z. Li 82 27 0 09 Jun 2023
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks Donald Loveland Jiong Zhu Mark Heimann Benjamin Fish Michael T. Shaub Danai Koutra 120 7 0 08 Jun 2023
$Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph$ Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph Camilo Ruiz Hongyu Ren Kexin Huang J. Leskovec 69 2 0 07 Jun 2023