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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
HetCAN: A Heterogeneous Graph Cascade Attention Network with Dual-Level Awareness Zeyuan Zhao Qingqing Ge Anfeng Cheng Yiding Liu Xiang Li Shuaiqiang Wang 38 0 0 06 Nov 2023
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach Tuan Nguyen Hirotada Honda Takashi Sano Vinh-Tiep Nguyen Shugo Nakamura Tan-Minh Nguyen 85 5 0 06 Nov 2023
Edge2Node: Reducing Edge Prediction to Node Classification Zahed Rahmati 21 0 0 06 Nov 2023
Distributed Matrix-Based Sampling for Graph Neural Network Training Alok Tripathy Katherine Yelick A. Buluç 63 4 0 06 Nov 2023
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning Xiaojun Guo Yifei Wang Zeming Wei Yisen Wang 103 12 0 05 Nov 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel Xuan Li Zhanke Zhou Jiangchao Yao Yu Rong Lu Zhang Bo Han 121 5 0 02 Nov 2023
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent Lorenz Kummer Samir Moustafa Nils N. Kriege Wilfried N. Gansterer GNN AAML 86 0 0 02 Nov 2023
Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks Jiarong Xu Renhong Huang Xin Jiang Yuxuan Cao Carl Yang Chunping Wang Yang Yang AI4CE 119 15 0 02 Nov 2023
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures Runa Eschenhagen Alexander Immer Richard Turner Frank Schneider Philipp Hennig 135 24 0 01 Nov 2023
Form follows Function: Text-to-Text Conditional Graph Generation based on Functional Requirements Peter Zachares Vahan Hovhannisyan Alan Mosca Yarin Gal 64 1 0 01 Nov 2023
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis Abhinav Nippani Dongyue Li Haotian Ju Haris N. Koutsopoulos Hongyang R. Zhang GNN 128 8 0 31 Oct 2023
Diversified Node Sampling based Hierarchical Transformer Pooling for Graph Representation Learning Gaichao Li Jinsong Chen John E. Hopcroft Kun He 46 0 0 31 Oct 2023
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes Cai Zhou Xiyuan Wang Muhan Zhang 70 17 0 30 Oct 2023
A Metadata-Driven Approach to Understand Graph Neural Networks Tinghong Li Qiaozhu Mei Jiaqi Ma AI4CE 89 5 0 30 Oct 2023
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network Lecheng Kong Jiarui Feng Hao Liu Dacheng Tao Yixin Chen Muhan Zhang AI4CE 64 12 0 29 Oct 2023
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? Yongqiang Chen Yatao Bian Kaiwen Zhou Binghui Xie Bo Han James Cheng OOD 109 41 0 29 Oct 2023
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach Nurendra Choudhary Nikhil S. Rao Chandan K. Reddy 56 7 0 29 Oct 2023
Simple and Asymmetric Graph Contrastive Learning without Augmentations Teng Xiao Huaisheng Zhu Zhengyu Chen Suhang Wang 89 35 0 29 Oct 2023
Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings Yi Ren Samuel Lavoie Mikhail Galkin Danica J. Sutherland Aaron Courville 86 16 0 28 Oct 2023
Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First Zhengwu Zhang Junxiang Wang Liang Zhao 75 13 0 28 Oct 2023
Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding Jiangyan Ma Yifei Wang Yisen Wang 109 14 0 28 Oct 2023
Disentangled Representation Learning with Large Language Models for Text-Attributed Graphs Yi Qin Xin Eric Wang Ziwei Zhang Wenwu Zhu AI4CE 77 34 0 27 Oct 2023
PSP: Pre-Training and Structure Prompt Tuning for Graph Neural Networks Qingqing Ge Zeyuan Zhao Yiding Liu Anfeng Cheng Xiang Li Shuaiqiang Wang D. Yin 73 7 0 26 Oct 2023
Unleashing the potential of GNNs via Bi-directional Knowledge Transfer Shuai Zheng Zhizhe Liu Zhenfeng Zhu Xingxing Zhang Jianxin Li Yao-Min Zhao 73 0 0 26 Oct 2023
RDBench: ML Benchmark for Relational Databases Zizhao Zhang Yi Yang Lutong Zou He Wen Tao Feng Jiaxuan You 59 3 0 25 Oct 2023
A Causal Disentangled Multi-Granularity Graph Classification Method Yuan Li Li Liu Penggang Chen Youmin Zhang Guoyin Wang 39 1 0 25 Oct 2023
ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation Anshul Ahluwalia Rohit Das Payman Behnam Alind Khare Pan Li Alexey Tumanov 109 2 0 24 Oct 2023
Graph Deep Learning for Time Series Forecasting Andrea Cini Ivan Marisca Daniele Zambon Cesare Alippi AI4TS AI4CE 126 16 0 24 Oct 2023
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs Yichuan Li Kaize Ding Kyumin Lee SSL 88 25 0 23 Oct 2023
ULTRA-DP: Unifying Graph Pre-training with Multi-task Graph Dual Prompt Mouxiang Chen Zemin Liu Chenghao Liu Jundong Li Qiheng Mao Jianling Sun AAML 88 14 0 23 Oct 2023
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules Zhiyuan Liu Yaorui Shi An Zhang Enzhi Zhang Kenji Kawaguchi Xiang Wang Tat-Seng Chua AI4CE 88 40 0 23 Oct 2023
Efficient Heterogeneous Graph Learning via Random Projection Jun Hu Bryan Hooi Bingsheng He 106 12 0 23 Oct 2023
Ensemble Learning for Graph Neural Networks Zhen Hao Wong Ling Yue Quanming Yao 94 0 0 22 Oct 2023
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? Mufei Li Eleonora Kreacic Vamsi K. Potluru Pan Li DiffM 86 10 0 20 Oct 2023
Pretraining Language Models with Text-Attributed Heterogeneous Graphs Tao Zou Le Yu Yifei Huang Leilei Sun Bo Du AI4CE 62 17 0 19 Oct 2023
Open-World Lifelong Graph Learning Marcel Hoffmann Lukas Galke A. Scherp 98 5 0 19 Oct 2023
GraphGPT: Graph Instruction Tuning for Large Language Models Jiabin Tang Yuhao Yang Wei Wei Lei Shi Lixin Su Suqi Cheng D. Yin Chao Huang 157 148 0 19 Oct 2023
Cooperative Minibatching in Graph Neural Networks M. F. Balin Dominique LaSalle Ümit V. Çatalyürek GNN 71 1 0 19 Oct 2023
MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy Haitian Jiang Renjie Liu Xiao Yan Zhenkun Cai Minjie Wang David Wipf Minjie Wang David Wipf GNN AI4CE 91 3 0 19 Oct 2023
Fast Graph Condensation with Structure-based Neural Tangent Kernel Lin Wang Wenqi Fan Jiatong Li Yao Ma Qing Li DD 92 31 0 17 Oct 2023
Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation Xin Gao Wentao Zhang Junliang Yu Yingxiao Shao Quoc Viet Hung Nguyen Tengjiao Wang Hongzhi Yin AI4CE GNN 116 10 0 17 Oct 2023
A Local Graph Limits Perspective on Sampling-Based GNNs Yeganeh Alimohammadi Luana Ruiz Amin Saberi 64 3 0 17 Oct 2023
Heterogenous Memory Augmented Neural Networks Zihan Qiu Zhen Liu Shuicheng Yan Shanghang Zhang Jie Fu 68 0 0 17 Oct 2023
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection Zhihao Ding Jieming Shi Shiqi Shen Xuequn Shang Jiannong Cao Zhipeng Wang Zhi Gong OODD OOD 101 4 0 16 Oct 2023
From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond Andi Han Dai Shi Lequan Lin Junbin Gao AI4CE GNN 107 24 0 16 Oct 2023
Score-Based Methods for Discrete Optimization in Deep Learning Eric Lei Arman Adibi Hamed Hassani 83 1 0 15 Oct 2023
Mirage: Model-Agnostic Graph Distillation for Graph Classification Mridul Gupta S. Manchanda H. Kodamana Sayan Ranu DD 89 16 0 14 Oct 2023
Graph Distillation with Eigenbasis Matching Yang Liu Deyu Bo Chuan Shi DD 140 10 0 13 Oct 2023
Does Graph Distillation See Like Vision Dataset Counterpart? Beining Yang Kai Wang Qingyun Sun Cheng Ji Xingcheng Fu Hao Tang Yang You Jianxin Li DD 71 45 0 13 Oct 2023
Relation-aware Ensemble Learning for Knowledge Graph Embedding Ling Yue Yongqi Zhang Quanming Yao Yong Li Xian Wu Ziheng Zhang Zhenxi Lin Yefeng Zheng 70 4 0 13 Oct 2023