Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification

18 January 2024

Roger Zimmermann

Papers citing "Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification"

35 / 35 papers shown

Title
DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks Zeyu Zhang Lu Li Shuyan Wan Sijie Wang Zhiyi Wang Zhiyuan Lu Dong Hao Wanli Li 55 2 0 29 Sep 2024
Graph Mixup with Soft Alignments Hongyi Ling Zhimeng Jiang Meng Liu Shuiwang Ji Na Zou AAML 46 21 0 11 Jun 2023
Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey G. Jin Yuxuan Liang Yuchen Fang Zezhi Shao Jincai Huang Junbo Zhang Yu Zheng AI4TS AI4CE 97 190 0 25 Mar 2023
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification Moshe Eliasof E. Haber Eran Treister GNN 68 0 0 29 Nov 2022
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum Nian Liu Xiao Wang Deyu Bo Chuan Shi Jian Pei 40 63 0 05 Oct 2022
Spectral Augmentation for Self-Supervised Learning on Graphs Lu Lin Jinghui Chen Hongning Wang OOD 58 49 0 02 Oct 2022
Model-Agnostic Augmentation for Accurate Graph Classification Jaemin Yoo Sooyeon Shim U. Kang GNN 63 29 0 21 Feb 2022
Graph Data Augmentation for Graph Machine Learning: A Survey Tong Zhao Wei Jin Yozen Liu Yingheng Wang Gang Liu Stephan Günnemann Neil Shah Meng Jiang OOD 74 80 0 17 Feb 2022
Data Augmentation for Deep Graph Learning: A Survey Kaize Ding Zhe Xu Hanghang Tong Huan Liu OOD GNN 77 223 0 16 Feb 2022
G-Mixup: Graph Data Augmentation for Graph Classification Xiaotian Han Zhimeng Jiang Ninghao Liu Xia Hu 62 195 0 15 Feb 2022
A New Perspective on the Effects of Spectrum in Graph Neural Networks Mingqi Yang Yanming Shen Rui Li Heng Qi Qian Zhang Baocai Yin GNN 28 28 0 14 Dec 2021
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 93 49 0 10 Nov 2021
Graph Contrastive Learning Automated Yuning You Tianlong Chen Yang Shen Zhangyang Wang 68 463 0 10 Jun 2021
Adversarial Graph Augmentation to Improve Graph Contrastive Learning Susheel Suresh Pan Li Cong Hao Jennifer Neville AAML 57 338 0 10 Jun 2021
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting Defu Cao Yujing Wang Juanyong Duan Ce Zhang Xia Zhu ... Yunhai Tong Bixiong Xu Jing Bai Jie Tong Qi Zhang AI4TS 39 509 0 13 Mar 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 161 573 0 04 Jan 2021
Graph signal processing for machine learning: A review and new perspectives Xiaowen Dong D. Thanou Laura Toni M. Bronstein P. Frossard 44 161 0 31 Jul 2020
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 189 808 0 16 Jul 2020
Contrastive Multi-View Representation Learning on Graphs Kaveh Hassani Amir Hosein Khas Ahmadi SSL 208 1,292 0 10 Jun 2020
Graph Random Neural Network for Semi-Supervised Learning on Graphs Wenzheng Feng Jie Zhang Yuxiao Dong Yu Han Huanbo Luan Qian Xu Qiang Yang Evgeny Kharlamov Jie Tang 79 391 0 22 May 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 259 2,701 0 02 May 2020
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 143 852 0 31 Jul 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 93 1,323 0 25 Jul 2019
Strategies for Pre-training Graph Neural Networks Weihua Hu Bowen Liu Joseph Gomes Marinka Zitnik Percy Liang Vijay S. Pande J. Leskovec SSL AI4CE 91 1,377 0 29 May 2019
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters Hoang NT Takanori Maehara GNN 83 427 0 23 May 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 199 7,554 0 01 Oct 2018
Deep Graph Infomax Petar Velickovic W. Fedus William L. Hamilton Pietro Lio Yoshua Bengio R. Devon Hjelm GNN 112 2,368 0 27 Sep 2018
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 258 9,687 0 25 Oct 2017
graph2vec: Learning Distributed Representations of Graphs A. Narayanan Mahinthan Chandramohan R. Venkatesan Lihui Chen Yang Liu Shantanu Jaiswal GNN 64 734 0 17 Jul 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 431 15,066 0 07 Jun 2017
Variational Graph Auto-Encoders Thomas Kipf Max Welling GNN BDL SSL CML 121 3,559 0 21 Nov 2016
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 141 2,911 0 07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 540 28,901 0 09 Sep 2016
node2vec: Scalable Feature Learning for Networks Aditya Grover J. Leskovec 172 10,825 0 03 Jul 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 293 7,622 0 30 Jun 2016