Data Augmentation for Graph Neural Networks

11 June 2020

Papers citing "Data Augmentation for Graph Neural Networks"

39 / 39 papers shown

Title
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Zihan Chen Xingbo Fu Yushun Dong Jundong Li Cong Shen FedML 69 0 0 29 Apr 2025
Rethinking Graph Structure Learning in the Era of LLMs Zhihan Zhang Xunkai Li Guang Zeng Hongchao Qin R. Li Guoren Wang 44 0 0 27 Mar 2025
Diffusion on Graph: Augmentation of Graph Structure for Node Classification Yancheng Wang Changyu Liu Yingzhen Yang DiffM GNN 68 0 0 16 Mar 2025
GraphFM: Graph Factorization Machines for Feature Interaction Modeling Shu Wu Zekun Li Yunyue Su Zeyu Cui Xiaoyu Zhang Liang Wang 64 22 0 24 Feb 2025
Graph Contrastive Learning on Multi-label Classification for Recommendations Jiayang Wu Wensheng Gan Huashen Lu Philip S. Yu 36 1 0 13 Jan 2025
Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting Lirong Wu Haitao Lin Guojiang Zhao Cheng Tan Stan Z. Li 16 0 0 09 Sep 2024
A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs Amitoz Azad Yuan Fang 32 1 0 01 Jul 2024
Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification Beini Xie Heng Chang Ziwei Zhang Zeyang Zhang Simin Wu Xin Wang Yuan Meng Wenwu Zhu 29 2 0 24 Jun 2024
Synergistic Deep Graph Clustering Network Benyu Wu Shifei Ding Xiao Xu Lili Guo Ling Ding Xindong Wu 28 0 0 22 Jun 2024
DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise Tai Hasegawa Sukwon Yun Xin Liu Yin Jun Phua Tsuyoshi Murata 21 0 0 14 Apr 2024
Physics-Enhanced Graph Neural Networks For Soft Sensing in Industrial Internet of Things Keivan Faghih Niresi Hugo Bissig Henri Baumann Olga Fink AI4CE 35 2 0 11 Apr 2024
How Does Message Passing Improve Collaborative Filtering? Mingxuan Ju William Shiao Zhichun Guo Yanfang Ye Yozen Liu Neil Shah Tong Zhao 24 4 0 27 Mar 2024
GraphEdit: Large Language Models for Graph Structure Learning Zirui Guo Lianghao Xia Yanhua Yu Yuling Wang Zixuan Yang Zhiyong Huang Chao Huang 39 18 0 23 Feb 2024
DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learning Seungyoon Choi Wonjoong Kim Sungwon Kim Yeonjun In Sein Kim Chanyoung Park CLL 22 4 0 21 Feb 2024
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching Federico Errica Henrik Christiansen Viktor Zaverkin Takashi Maruyama Mathias Niepert Francesco Alesiani 45 6 0 27 Dec 2023
DropMix: Better Graph Contrastive Learning with Harder Negative Samples Yueqi Ma Minjie Chen Xiang Li SSL 15 1 0 15 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 25 21 0 10 Oct 2023
Self-attention Dual Embedding for Graphs with Heterophily Yurui Lai Taiyan Zhang Rui Fan GNN 27 0 0 28 May 2023
Boosting long-term forecasting performance for continuous-time dynamic graph networks via data augmentation Yu Tian Mingjie Zhu Jiachi Luo Song Li 13 0 0 12 Apr 2023
Dynamic Graph Representation Learning with Neural Networks: A Survey Leshanshui Yang Sébastien Adam Clément Chatelain AI4TS AI4CE 26 14 0 12 Apr 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 22 88 0 27 Dec 2022
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation Zhihao Zhu Chenwang Wu Mingyang Zhou Hao Liao DefuLian Enhong Chen AAML 11 4 0 15 Nov 2022
Robust Training of Graph Neural Networks via Noise Governance Siyi Qian Haochao Ying Renjun Hu Jingbo Zhou Jintai Chen D. Z. Chen Jian Wu NoLa 19 34 0 12 Nov 2022
Self-Supervised Graph Structure Refinement for Graph Neural Networks Jianan Zhao Qianlong Wen Mingxuan Ju Chuxu Zhang Yanfang Ye 21 20 0 12 Nov 2022
TuneUp: A Simple Improved Training Strategy for Graph Neural Networks Weihua Hu Kaidi Cao Kexin Huang E-Wen Huang Karthik Subbian Kenji Kawaguchi J. Leskovec 24 0 0 26 Oct 2022
MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentation Zeming Dong Qiang Hu Yuejun Guo Maxime Cordy Mike Papadakis Zhenya Zhang Yves Le Traon Jianjun Zhao 18 8 0 06 Oct 2022
Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model Haoteng Tang Guixiang Ma Lei Guo Xiyao Fu Heng-Chiao Huang L. Zhang 16 24 0 14 Jul 2022
Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN Kuan Li Yang Liu Xiang Ao Jianfeng Chi Jinghua Feng Hao Yang Qing He AAML 36 62 0 30 Jun 2022
Condensing Graphs via One-Step Gradient Matching Wei Jin Xianfeng Tang Haoming Jiang Zheng Li Danqing Zhang Jiliang Tang Bin Ying DD 21 97 0 15 Jun 2022
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective Wei Jin Xiaorui Liu Yao Ma Charu C. Aggarwal Jiliang Tang 24 41 0 15 Jun 2022
Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting Jiabin Tang Tang Qian Shikun Liu Shengdong Du Jie Hu Tianrui Li AI4TS 22 21 0 25 Feb 2022
Deep Graph Learning for Anomalous Citation Detection Jiaying Liu Feng Xia Xu Feng Jing Ren Huan Liu 22 40 0 23 Feb 2022
Model-Agnostic Augmentation for Accurate Graph Classification Jaemin Yoo Sooyeon Shim U. Kang GNN 14 29 0 21 Feb 2022
Imbalanced Graph Classification via Graph-of-Graph Neural Networks Yu-Chiang Frank Wang Yuying Zhao Neil Shah Tyler Derr 25 47 0 01 Dec 2021
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 79 49 0 10 Nov 2021
InfoGCL: Information-Aware Graph Contrastive Learning Dongkuan Xu Wei Cheng Dongsheng Luo Haifeng Chen Xiang Zhang 22 190 0 28 Oct 2021
A Unified View on Graph Neural Networks as Graph Signal Denoising Yao Ma Xiaorui Liu Tong Zhao Yozen Liu Jiliang Tang Neil Shah AI4CE 20 175 0 05 Oct 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 229 1,935 0 09 Jun 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,809 0 25 Nov 2016