v1v2v3v4 (latest)

Graph Random Neural Network for Semi-Supervised Learning on Graphs

22 May 2020

Yuxiao Dong

ArXiv (abs)PDF HTML Github (210★)

Papers citing "Graph Random Neural Network for Semi-Supervised Learning on Graphs"

50 / 186 papers shown

Title
Comparative Analysis of Radiomic Features and Gene Expression Profiles in Histopathology Data Using Graph Neural Networks Luis Carlos Rivera Monroy Leonhard Rist Martin Eberhardt C. Ostalecki Andreas Bauer Julio Vera Katharina Breininger Andreas Maier MedIm 38 1 0 25 Dec 2023
Robust Node Representation Learning via Graph Variational Diffusion Networks Jun Zhuang M. A. Hasan 71 7 0 18 Dec 2023
Sparse but Strong: Crafting Adversarially Robust Graph Lottery Tickets Subhajit Dutta Chowdhury Zhiyu Ni Qingyuan Peng Souvik Kundu Pierluigi Nuzzo 83 3 0 11 Dec 2023
Factorized Explainer for Graph Neural Networks Rundong Huang Farhad Shirani Dongsheng Luo 92 10 0 09 Dec 2023
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts Shirley Wu Kaidi Cao Bruno Ribeiro James Zou J. Leskovec OOD 76 3 0 07 Dec 2023
Robust Graph Neural Networks via Unbiased Aggregation Ruiqi Feng Zhichao Hou Hanyu Wang Xiaorui Liu 90 0 0 25 Nov 2023
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study Kush Kothari Bhavya Mehta Reshmika Nambiar S. Shrawne 73 0 0 21 Nov 2023
Unleashing the potential of GNNs via Bi-directional Knowledge Transfer Shuai Zheng Zhizhe Liu Zhenfeng Zhu Xingxing Zhang Jianxin Li Yao-Min Zhao 75 0 0 26 Oct 2023
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach Kai Zhao Qiyu Kang Yang Song Rui She Sijie Wang Wee Peng Tay AAML 100 25 0 10 Oct 2023
Nonlinear Correct and Smooth for Semi-Supervised Learning Yuanhang Shao Xiuwen Liu 64 1 0 09 Oct 2023
Data-centric Graph Learning: A Survey Jixi Liu Deyu Bo Cheng Yang Haoran Dai Qi Zhang Yixin Xiao Yufei Peng Chuan Shi GNN 104 21 0 08 Oct 2023
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation Mingxuan Ju Tong Zhao Wenhao Yu Neil Shah Yanfang Ye 98 17 0 01 Oct 2023
Learning How to Propagate Messages in Graph Neural Networks Teng Xiao Zhengyu Chen Donglin Wang Suhang Wang GNN 101 80 0 01 Oct 2023
From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited Zheng Wang H. Ding Leyi Pan Jianhua Li Zhiguo Gong Philip S. Yu GNN 97 6 0 24 Sep 2023
Towards Data-centric Graph Machine Learning: Review and Outlook Xin Zheng Yixin Liu Zhifeng Bao Meng Fang Xia Hu Alan Wee-Chung Liew Shirui Pan GNN AI4CE 102 20 0 20 Sep 2023
Half-Hop: A graph upsampling approach for slowing down message passing Mehdi Azabou Venkataraman Ganesh S. Thakoor Chi-Heng Lin Lakshmi Sathidevi Ran Liu Michal Valko Petar Velickovic Eva L. Dyer 99 23 0 17 Aug 2023
Simple and Efficient Partial Graph Adversarial Attack: A New Perspective Guanghui Zhu Meng Chen Chun Yuan Jiaming Ji AAML 69 7 0 15 Aug 2023
Language is All a Graph Needs Ruosong Ye Caiqi Zhang Runhui Wang Shuyuan Xu Yongfeng Zhang AI4CE 176 171 0 14 Aug 2023
Addressing the Impact of Localized Training Data in Graph Neural Networks S. Akansha 80 3 0 24 Jul 2023
Collaborative Graph Neural Networks for Attributed Network Embedding Qiaoyu Tan Xin Zhang Xiao Shi Huang Haojun Chen Jundong Li Helen Zhou 148 12 0 22 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
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
Similarity Preserving Adversarial Graph Contrastive Learning Yeonjun In Kanghoon Yoon Chanyoung Park AAML 88 10 0 24 Jun 2023
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization Xiner Li Shurui Gui Youzhi Luo Shuiwang Ji OODD OOD 93 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
DualHGNN: A Dual Hypergraph Neural Network for Semi-Supervised Node Classification based on Multi-View Learning and Density Awareness Jianpeng Liao Jun Yan Qian Tao 63 2 0 07 Jun 2023
BeMap: Balanced Message Passing for Fair Graph Neural Network Xiao Lin Jian Kang Weilin Cong Hanghang Tong MoE 110 8 0 07 Jun 2023
Subgraph Networks Based Contrastive Learning Jinhuan Wang Jiafei Shao Zeyu Wang Shanqing Yu Qi Xuan Xiaoniu Yang 81 1 0 06 Jun 2023
Can Directed Graph Neural Networks be Adversarially Robust? Zhichao Hou Xitong Zhang Wei Wang Charu C. Aggarwal Xiaorui Liu AAML 71 1 0 03 Jun 2023
EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost Jaeseung Heo Seungbeom Lee SungSoo Ahn Dongwoo Kim 83 1 0 02 Jun 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
Unifying gradient regularization for Heterogeneous Graph Neural Networks Xiao Yang Xuejiao Zhao Zhiqi Shen 144 0 0 25 May 2023
Tokenized Graph Transformer with Neighborhood Augmentation for Node Classification in Large Graphs Jinsong Chen Chang-Shu Liu Kai-Xin Gao Gaichao Li Kun He 99 4 0 22 May 2023
ID-MixGCL: Identity Mixup for Graph Contrastive Learning Gehang Zhang Yu Bowen Jiangxia Cao Xinghua Zhang Shuaiyi Nie Chuan Zhou Tingwen Liu 149 0 0 20 Apr 2023
GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner Zhenyu Hou Yufei He Yukuo Cen Xiao Liu Yuxiao Dong Evgeny Kharlamov Jie Tang SSL 68 118 0 10 Apr 2023
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization Dongcheng Zou Hao Peng Xiang Huang Renyu Yang Jianxin Li Hongzhi Zhang Chun-Yi Liu Philip S. Yu 89 52 0 17 Mar 2023
Node-Specific Space Selection via Localized Geometric Hyperbolicity in Graph Neural Networks See Hian Lee Feng Ji Wee Peng Tay 70 1 0 03 Mar 2023
Framelet Message Passing Xinliang Liu Bingxin Zhou Chutian Zhang Yu Guang Wang 77 5 0 28 Feb 2023
Pseudo Contrastive Learning for Graph-based Semi-supervised Learning Weigang Lu Ziyu Guan Wei Zhao Yaming Yang Yuanhai Lv Lining Xing Baosheng Yu Dacheng Tao 118 7 0 19 Feb 2023
Building Shortcuts between Distant Nodes with Biaffine Mapping for Graph Convolutional Networks Acong Zhang Jincheng Huang Ping Li Kaizheng Zhang GNN 78 4 0 17 Feb 2023
DRGCN: Dynamic Evolving Initial Residual for Deep Graph Convolutional Networks Lefei Zhang Xiaodong Yan Jianshan He Ruopeng Li Wei Chu GNN 71 13 0 10 Feb 2023
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing Yunchong Song Cheng Zhou Xinbing Wang Zhouhan Lin 109 72 0 03 Feb 2023
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization Hengrui Zhang Shen Wang V. Ioannidis Soji Adeshina Jiani Zhang Xiao Qin Christos Faloutsos Da Zheng George Karypis Philip S. Yu 78 4 0 31 Jan 2023
Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic Simon Geisler Stephan Günnemann Aleksandar Bojchevski OOD AAML 96 59 0 31 Jan 2023
Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective Jiayuan Chen Xiang Zhang Yinfei Xu Tianli Zhao Renjie Xie Wei Xu GNN BDL 59 0 0 25 Jan 2023
Data Augmentation on Graphs: A Technical Survey Jiajun Zhou Chenxuan Xie Shengbo Gong Z. Wen Xiangyu Zhao Qi Xuan Xiaoniu Yang AI4TS 89 9 0 20 Dec 2022
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning Xumeng Gong Cheng Yang Chuan Shi VLM 72 44 0 14 Dec 2022
Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View Jingcan Duan Siwei Wang Pei Zhang En Zhu Jingtao Hu Huan Jin Yue Liu Zhibin Dong 74 91 0 01 Dec 2022
Semi-Supervised Heterogeneous Graph Learning with Multi-level Data Augmentation Yingxi Chen Siwei Qiang Mingming Ha Xiaolei Liu Shaoshuai Li Lingfeng Yuan Xiaobo Guo Zheng Hua Zhu 88 2 0 30 Nov 2022
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification Moshe Eliasof E. Haber Eran Treister GNN 112 0 0 29 Nov 2022