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v1v2 (latest)

Stability and Generalization of Graph Convolutional Neural Networks

Knowledge Discovery and Data Mining (KDD), 2019

3 May 2019

Papers citing "Stability and Generalization of Graph Convolutional Neural Networks"

45 / 95 papers shown

Title
Super-model ecosystem: A domain-adaptation perspective Fengxiang He Dacheng Tao DiffM 166 1 0 30 Aug 2022
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology SamplingInternational Conference on Machine Learning (ICML), 2022 Hongkang Li Ming Wang Sijia Liu Pin-Yu Chen Jinjun Xiong GNN 184 33 0 07 Jul 2022
Learning Enhanced Representations for Tabular Data via Neighborhood Propagation Kounianhua Du Weinan Zhang Ruiwen Zhou Yangkun Wang Xilong Zhao Jiarui Jin Quan Gan Zheng Zhang David Wipf AI4TS 121 9 0 14 Jun 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 212 82 0 16 Apr 2022
Graph Convolutional Neural Networks Sensitivity under Probabilistic Error ModelIEEE Transactions on Signal and Information Processing over Networks (TSIPN), 2022 Xinjue Wang Esa Ollila S. Vorobyov AAML 352 4 0 15 Mar 2022
Shift-Robust Node Classification via Graph Adversarial Clustering Qi Zhu Chao Zhang Chanyoung Park Carl Yang Jiawei Han OOD 150 6 0 07 Mar 2022
Out-Of-Distribution Generalization on Graphs: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 396 118 0 16 Feb 2022
Generalization Analysis of Message Passing Neural Networks on Large Random GraphsNeural Information Processing Systems (NeurIPS), 2022 Sohir Maskey Ron Levie Yunseok Lee Gitta Kutyniok GNN 630 62 0 01 Feb 2022
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks Pascal Esser L. C. Vankadara Debarghya Ghoshdastidar 151 63 0 07 Dec 2021
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OODD OOD 298 133 0 07 Dec 2021
$p$ -Laplacian Based Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2021 Guoji Fu P. Zhao Yatao Bian 176 49 0 14 Nov 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph ParametersNeural Information Processing Systems (NeurIPS), 2021 Takanori Maehara Hoang NT 184 3 0 05 Nov 2021
Graph Structural Attack by Perturbing Spectral DistanceKnowledge Discovery and Data Mining (KDD), 2021 Lu Lin Ethan Blaser Hongning Wang AAML 259 36 0 01 Nov 2021
On Provable Benefits of Depth in Training Graph Convolutional NetworksNeural Information Processing Systems (NeurIPS), 2021 Weilin Cong M. Ramezani M. Mahdavi 168 89 0 28 Oct 2021
Towards Open-World Feature Extrapolation: An Inductive Graph Learning ApproachNeural Information Processing Systems (NeurIPS), 2021 Qitian Wu Chenxiao Yang Junchi Yan 157 35 0 09 Oct 2021
Graph Neural Networks: Methods, Applications, and Opportunities Lilapati Waikhom Ripon Patgiri GNN 274 48 0 24 Aug 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural NetworksACM Computing Surveys (CSUR), 2021 Zhiqian Chen Fanglan Chen Lei Zhang Taoran Ji Kaiqun Fu Bo Pan Feng Chen Lingfei Wu Charu C. Aggarwal Chang-Tien Lu 643 33 0 21 Jul 2021
Subgroup Generalization and Fairness of Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2021 Jiaqi Ma Junwei Deng Qiaozhu Mei 243 91 0 29 Jun 2021
Stability to Deformations of Manifold Filters and Manifold Neural NetworksIEEE Transactions on Signal Processing (IEEE TSP), 2021 Zhiyang Wang Luana Ruiz Alejandro Ribeiro AAML 125 10 0 07 Jun 2021
Low-Rank Projections of GCNs Laplacian Nathan Grinsztajn Philippe Preux Edouard Oyallon 140 1 0 04 Jun 2021
Graph-based Semi-supervised Learning: A Comprehensive ReviewIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 Zixing Song Xiangli Yang Zenglin Xu Irwin King 300 266 0 26 Feb 2021
Generalization bounds for graph convolutional neural networks via Rademacher complexity Shaogao Lv GNN 158 20 0 20 Feb 2021
Robustness, Privacy, and Generalization of Adversarial Training Fengxiang He Shaopeng Fu Bohan Wang Dacheng Tao 240 12 0 25 Dec 2020
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural NetworksInternational Conference on Learning Representations (ICLR), 2020 Renjie Liao R. Urtasun R. Zemel 215 103 0 14 Dec 2020
On the Stability of Graph Convolutional Neural Networks under Edge RewiringIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 Henry Kenlay D. Thanou Xiaowen Dong 197 35 0 26 Oct 2020
From Local Structures to Size Generalization in Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2020 Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 470 158 0 17 Oct 2020
Computing Graph Neural Networks: A Survey from Algorithms to AcceleratorsACM Computing Surveys (ACM CSUR), 2020 S. Abadal Akshay Jain Robert Guirado Jorge López-Alonso Eduard Alarcón GNN 464 266 0 30 Sep 2020
Transfer Learning of Graph Neural Networks with Ego-graph Information MaximizationNeural Information Processing Systems (NeurIPS), 2020 Qi Zhu Carl Yang Yidan Xu Haonan Wang Chao Zhang Jiawei Han 349 131 0 11 Sep 2020
Learning Node Representations against PerturbationsPattern Recognition (Pattern Recognit.), 2020 Xu Chen Yuangang Pan Ivor Tsang Ya Zhang 191 4 0 26 Aug 2020
Tighter Generalization Bounds for Iterative Differentially Private Learning AlgorithmsConference on Uncertainty in Artificial Intelligence (UAI), 2020 Fengxiang He Bohan Wang Dacheng Tao FedML 204 20 0 18 Jul 2020
Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent Lauren Watson Benedek Rozemberczki Rik Sarkar 109 1 0 25 Jun 2020
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer CaseInternational Conference on Machine Learning (ICML), 2020 Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong MLT AI4CE 179 35 0 25 Jun 2020
Understanding Deep Architectures with Reasoning LayerNeural Information Processing Systems (NeurIPS), 2020 Xinshi Chen Yufei Zhang C. Reisinger Le Song AI4CE 247 8 0 24 Jun 2020
Quantifying Challenges in the Application of Graph Representation Learning Antonia Gogoglou C. Bayan Bruss Brian Nguyen Reza Sarshogh Keegan E. Hines 106 2 0 18 Jun 2020
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks Kenta Oono Taiji Suzuki AI4CE 408 33 0 15 Jun 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 328 323 0 07 May 2020
Generalization and Representational Limits of Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2020 Vikas Garg Stefanie Jegelka Tommi Jaakkola GNN 264 344 0 14 Feb 2020
The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short VersionInternational Symposium on Information Theory (ISIT), 2019 Abram Magner Mayank Baranwal Alfred Hero GNN 133 14 0 13 Feb 2020
Fundamental Limits of Deep Graph Convolutional Networks Abram Magner Mayank Baranwal Alfred Hero GNN 173 7 0 28 Oct 2019
Understanding Isomorphism Bias in Graph Data Sets Sergei Ivanov Sergei Sviridov Evgeny Burnaev FaML AI4CE 293 41 0 26 Oct 2019
Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning Saurabh Verma Zhi-Li Zhang FedML GNN SSL 258 10 0 22 Sep 2019
Understanding the Representation Power of Graph Neural Networks in Learning Graph TopologyNeural Information Processing Systems (NeurIPS), 2019 Nima Dehmamy Albert-László Barabási Rose Yu GNN 203 149 0 11 Jul 2019
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification Kenta Oono Taiji Suzuki GNN 327 30 0 27 May 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 2.1K 6,370 0 20 Dec 2018
Deep Learning on Graphs: A Survey Ziwei Zhang Peng Cui Wenwu Zhu GNN 440 1,487 0 11 Dec 2018

v1v2 (latest)

Stability and Generalization of Graph Convolutional Neural Networks

Knowledge Discovery and Data Mining (KDD), 2019

3 May 2019

Papers citing "Stability and Generalization of Graph Convolutional Neural Networks"

45 / 95 papers shown

Title
Super-model ecosystem: A domain-adaptation perspective Fengxiang He Dacheng Tao DiffM 166 1 0 30 Aug 2022
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology SamplingInternational Conference on Machine Learning (ICML), 2022 Hongkang Li Ming Wang Sijia Liu Pin-Yu Chen Jinjun Xiong GNN 184 33 0 07 Jul 2022
Learning Enhanced Representations for Tabular Data via Neighborhood Propagation Kounianhua Du Weinan Zhang Ruiwen Zhou Yangkun Wang Xilong Zhao Jiarui Jin Quan Gan Zheng Zhang David Wipf AI4TS 121 9 0 14 Jun 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 212 82 0 16 Apr 2022
Graph Convolutional Neural Networks Sensitivity under Probabilistic Error ModelIEEE Transactions on Signal and Information Processing over Networks (TSIPN), 2022 Xinjue Wang Esa Ollila S. Vorobyov AAML 352 4 0 15 Mar 2022
Shift-Robust Node Classification via Graph Adversarial Clustering Qi Zhu Chao Zhang Chanyoung Park Carl Yang Jiawei Han OOD 150 6 0 07 Mar 2022
Out-Of-Distribution Generalization on Graphs: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 396 118 0 16 Feb 2022
Generalization Analysis of Message Passing Neural Networks on Large Random GraphsNeural Information Processing Systems (NeurIPS), 2022 Sohir Maskey Ron Levie Yunseok Lee Gitta Kutyniok GNN 630 62 0 01 Feb 2022
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks Pascal Esser L. C. Vankadara Debarghya Ghoshdastidar 151 63 0 07 Dec 2021
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OODD OOD 298 133 0 07 Dec 2021
$p$ -Laplacian Based Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2021 Guoji Fu P. Zhao Yatao Bian 176 49 0 14 Nov 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph ParametersNeural Information Processing Systems (NeurIPS), 2021 Takanori Maehara Hoang NT 184 3 0 05 Nov 2021
Graph Structural Attack by Perturbing Spectral DistanceKnowledge Discovery and Data Mining (KDD), 2021 Lu Lin Ethan Blaser Hongning Wang AAML 259 36 0 01 Nov 2021
On Provable Benefits of Depth in Training Graph Convolutional NetworksNeural Information Processing Systems (NeurIPS), 2021 Weilin Cong M. Ramezani M. Mahdavi 168 89 0 28 Oct 2021
Towards Open-World Feature Extrapolation: An Inductive Graph Learning ApproachNeural Information Processing Systems (NeurIPS), 2021 Qitian Wu Chenxiao Yang Junchi Yan 157 35 0 09 Oct 2021
Graph Neural Networks: Methods, Applications, and Opportunities Lilapati Waikhom Ripon Patgiri GNN 274 48 0 24 Aug 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural NetworksACM Computing Surveys (CSUR), 2021 Zhiqian Chen Fanglan Chen Lei Zhang Taoran Ji Kaiqun Fu Bo Pan Feng Chen Lingfei Wu Charu C. Aggarwal Chang-Tien Lu 643 33 0 21 Jul 2021
Subgroup Generalization and Fairness of Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2021 Jiaqi Ma Junwei Deng Qiaozhu Mei 243 91 0 29 Jun 2021
Stability to Deformations of Manifold Filters and Manifold Neural NetworksIEEE Transactions on Signal Processing (IEEE TSP), 2021 Zhiyang Wang Luana Ruiz Alejandro Ribeiro AAML 125 10 0 07 Jun 2021
Low-Rank Projections of GCNs Laplacian Nathan Grinsztajn Philippe Preux Edouard Oyallon 140 1 0 04 Jun 2021
Graph-based Semi-supervised Learning: A Comprehensive ReviewIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 Zixing Song Xiangli Yang Zenglin Xu Irwin King 300 266 0 26 Feb 2021
Generalization bounds for graph convolutional neural networks via Rademacher complexity Shaogao Lv GNN 158 20 0 20 Feb 2021
Robustness, Privacy, and Generalization of Adversarial Training Fengxiang He Shaopeng Fu Bohan Wang Dacheng Tao 240 12 0 25 Dec 2020
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural NetworksInternational Conference on Learning Representations (ICLR), 2020 Renjie Liao R. Urtasun R. Zemel 215 103 0 14 Dec 2020
On the Stability of Graph Convolutional Neural Networks under Edge RewiringIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 Henry Kenlay D. Thanou Xiaowen Dong 197 35 0 26 Oct 2020
From Local Structures to Size Generalization in Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2020 Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 470 158 0 17 Oct 2020
Computing Graph Neural Networks: A Survey from Algorithms to AcceleratorsACM Computing Surveys (ACM CSUR), 2020 S. Abadal Akshay Jain Robert Guirado Jorge López-Alonso Eduard Alarcón GNN 464 266 0 30 Sep 2020
Transfer Learning of Graph Neural Networks with Ego-graph Information MaximizationNeural Information Processing Systems (NeurIPS), 2020 Qi Zhu Carl Yang Yidan Xu Haonan Wang Chao Zhang Jiawei Han 349 131 0 11 Sep 2020
Learning Node Representations against PerturbationsPattern Recognition (Pattern Recognit.), 2020 Xu Chen Yuangang Pan Ivor Tsang Ya Zhang 191 4 0 26 Aug 2020
Tighter Generalization Bounds for Iterative Differentially Private Learning AlgorithmsConference on Uncertainty in Artificial Intelligence (UAI), 2020 Fengxiang He Bohan Wang Dacheng Tao FedML 204 20 0 18 Jul 2020
Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent Lauren Watson Benedek Rozemberczki Rik Sarkar 109 1 0 25 Jun 2020
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer CaseInternational Conference on Machine Learning (ICML), 2020 Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong MLT AI4CE 179 35 0 25 Jun 2020
Understanding Deep Architectures with Reasoning LayerNeural Information Processing Systems (NeurIPS), 2020 Xinshi Chen Yufei Zhang C. Reisinger Le Song AI4CE 247 8 0 24 Jun 2020
Quantifying Challenges in the Application of Graph Representation Learning Antonia Gogoglou C. Bayan Bruss Brian Nguyen Reza Sarshogh Keegan E. Hines 106 2 0 18 Jun 2020
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks Kenta Oono Taiji Suzuki AI4CE 408 33 0 15 Jun 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 328 323 0 07 May 2020
Generalization and Representational Limits of Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2020 Vikas Garg Stefanie Jegelka Tommi Jaakkola GNN 264 344 0 14 Feb 2020
The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short VersionInternational Symposium on Information Theory (ISIT), 2019 Abram Magner Mayank Baranwal Alfred Hero GNN 133 14 0 13 Feb 2020
Fundamental Limits of Deep Graph Convolutional Networks Abram Magner Mayank Baranwal Alfred Hero GNN 173 7 0 28 Oct 2019
Understanding Isomorphism Bias in Graph Data Sets Sergei Ivanov Sergei Sviridov Evgeny Burnaev FaML AI4CE 293 41 0 26 Oct 2019
Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning Saurabh Verma Zhi-Li Zhang FedML GNN SSL 258 10 0 22 Sep 2019
Understanding the Representation Power of Graph Neural Networks in Learning Graph TopologyNeural Information Processing Systems (NeurIPS), 2019 Nima Dehmamy Albert-László Barabási Rose Yu GNN 203 149 0 11 Jul 2019
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification Kenta Oono Taiji Suzuki GNN 327 30 0 27 May 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 2.1K 6,370 0 20 Dec 2018
Deep Learning on Graphs: A Survey Ziwei Zhang Peng Cui Wenwu Zhu GNN 440 1,487 0 11 Dec 2018