Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization

13 February 2021

Papers citing "Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization"

50 / 55 papers shown

Title
A Pre-Training and Adaptive Fine-Tuning Framework for Graph Anomaly Detection Yunhui Liu Jiashun Cheng Jia Li Fugee Tsung Hongzhi Yin Tieke He 29 0 0 19 Apr 2025
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model O. Duranthon L. Zdeborová 41 0 0 03 Mar 2025
Unveiling Mode Connectivity in Graph Neural Networks Bingheng Li Z. Chen Haoyu Han Shenglai Zeng J. Liu Jiliang Tang 36 0 0 18 Feb 2025
Optimality of Message-Passing Architectures for Sparse Graphs Aseem Baranwal K. Fountoulakis Aukosh Jagannath 73 11 0 10 Jan 2025
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks Hai-Xiao Wang Zhichao Wang 71 1 0 18 Dec 2024
Mixture of Experts for Node Classification Yu Shi Yiqi Wang WeiXuan Lang Jiaxin Zhang Pan Dong Aiping Li 124 0 0 30 Nov 2024
Learning Personalized Scoping for Graph Neural Networks under Heterophily Gangda Deng Hongkuan Zhou R. Kannan Viktor Prasanna 31 0 0 11 Sep 2024
Generalization of Graph Neural Networks is Robust to Model Mismatch Zhiyang Wang J. Cerviño Alejandro Ribeiro 40 1 0 25 Aug 2024
Joint Graph Rewiring and Feature Denoising via Spectral Resonance Jonas Linkerhagner Cheng Shi Ivan Dokmanić 33 0 0 13 Aug 2024
Better Not to Propagate: Understanding Edge Uncertainty and Over-smoothing in Signed Graph Neural Networks Yoonhyuk Choi Jiho Choi Taewook Ko Chong-Kwon Kim 41 0 0 09 Aug 2024
Introducing Diminutive Causal Structure into Graph Representation Learning Hang Gao Peng Qiao Yifan Jin Fengge Wu Jiangmeng Li Changwen Zheng 22 4 0 13 Jun 2024
Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach Haoyu Han Juanhui Li Wei Huang Xianfeng Tang Hanqing Lu Chen Luo Hui Liu Jiliang Tang 33 5 0 05 Jun 2024
Analysis of Corrected Graph Convolutions Robert Wang Aseem Baranwal K. Fountoulakis 29 0 0 22 May 2024
On the Topology Awareness and Generalization Performance of Graph Neural Networks Junwei Su Chuan Wu AI4CE 24 0 0 07 Mar 2024
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning Man Wu Xin-Yang Zheng Qin Zhang Xiao Shen Xiong Luo Xingquan Zhu Shirui Pan OOD 65 6 0 26 Feb 2024
Weisfeiler-Leman at the margin: When more expressivity matters Billy J. Franks Christopher Morris A. Velingker Floris Geerts 50 9 0 12 Feb 2024
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective Soo Yong Lee Sunwoo Kim Fanchen Bu Jaemin Yoo Jiliang Tang Kijung Shin 40 6 0 07 Feb 2024
Asymptotic generalization error of a single-layer graph convolutional network O. Duranthon L. Zdeborová MLT 35 2 0 06 Feb 2024
Understanding Heterophily for Graph Neural Networks Junfu Wang Yuanfang Guo Liang Yang Yun-an Wang 26 10 0 17 Jan 2024
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs Pengfei Ding Yan Wang Guanfeng Liu Nan Wang Xiaofang Zhou OODD OOD 18 2 0 07 Jan 2024
Understanding Community Bias Amplification in Graph Representation Learning Shengzhong Zhang Wenjie Yang Yimin Zhang Hongwei Zhang Divin Yan Zengfeng Huang FaML 16 0 0 08 Dec 2023
GGNNs : Generalizing GNNs using Residual Connections and Weighted Message Passing Abhinav Raghuvanshi K. Malleshappa AI4CE GNN 17 0 0 26 Nov 2023
A Metadata-Driven Approach to Understand Graph Neural Networks Tinghong Li Qiaozhu Mei Jiaqi Ma AI4CE 16 5 0 30 Oct 2023
Global Minima, Recoverability Thresholds, and Higher-Order Structure in GNNS Drake Brown Trevor Garrity Kaden Parker Jason Oliphant Stone Carson Cole Hanson Zachary Boyd 16 0 0 11 Oct 2023
How Graph Neural Networks Learn: Lessons from Training Dynamics Chenxiao Yang Qitian Wu David Wipf Ruoyu Sun Junchi Yan AI4CE GNN 14 1 0 08 Oct 2023
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective Wei Huang Yuanbin Cao Hong Wang Xin Cao Taiji Suzuki MLT 17 6 0 24 Jun 2023
Optimal Inference in Contextual Stochastic Block Models O. Duranthon L. Zdeborová BDL 35 8 0 06 Jun 2023
Explaining and Adapting Graph Conditional Shift Qi Zhu Yizhu Jiao Natalia Ponomareva Jiawei Han Bryan Perozzi OOD 13 10 0 05 Jun 2023
Towards Deep Attention in Graph Neural Networks: Problems and Remedies Soo Yong Lee Fanchen Bu Jaemin Yoo Kijung Shin GNN 9 30 0 04 Jun 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? Haitao Mao Zhikai Chen Wei Jin Haoyu Han Yao Ma Tong Zhao Neil Shah Jiliang Tang 23 31 0 02 Jun 2023
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding Nicolas Keriven Samuel Vaiter 29 11 0 24 May 2023
Learning for Transductive Threshold Calibration in Open-World Recognition Q. Zhang Dongsheng An Tianjun Xiao Tong He Qingming Tang Ying Nian Wu Joseph Tighe Yifan Xing Stefano Soatto 19 0 0 19 May 2023
Revisiting Robustness in Graph Machine Learning Lukas Gosch Daniel Sturm Simon Geisler Stephan Günnemann AAML OOD 61 21 0 01 May 2023
When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability Sitao Luan Chenqing Hua Minkai Xu Qincheng Lu Jiaqi Zhu Xiaoming Chang Jie Fu J. Leskovec Doina Precup 31 3 0 25 Apr 2023
Mind the Label Shift of Augmentation-based Graph OOD Generalization Junchi Yu Jian Liang R. He 34 27 0 27 Mar 2023
Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective Hang Gao Jiangmeng Li Wenwen Qiang Lingyu Si Xingzhe Su Feng Wu Changwen Zheng Fuchun Sun 19 0 0 20 Jan 2023
Homophily modulates double descent generalization in graph convolution networks Chengzhi Shi Liming Pan Hong Hu Ivan Dokmanić 28 9 0 26 Dec 2022
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks X. Wu Zhengdao Chen W. Wang Ali Jadbabaie 17 38 0 21 Dec 2022
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs Chenxiao Yang Qitian Wu Jiahua Wang Junchi Yan AI4CE 13 51 0 18 Dec 2022
Learnable Graph Convolutional Attention Networks Adrián Javaloy Pablo Sánchez-Martín Amit Levi Isabel Valera GNN 19 10 0 21 Nov 2022
Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph Hong Wang Jieyu Zhang Qi Zhu Wei Huang Kenji Kawaguchi X. Xiao 26 11 0 20 Nov 2022
A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs Luana Ruiz Ningyuan Huang Soledad Villar 19 5 0 06 Nov 2022
On Classification Thresholds for Graph Attention with Edge Features K. Fountoulakis Dake He Silvio Lattanzi Bryan Perozzi Anton Tsitsulin Shenghao Yang GNN 10 6 0 18 Oct 2022
Finding Diverse and Predictable Subgraphs for Graph Domain Generalization Junchi Yu Jian Liang Ran He OOD 10 11 0 19 Jun 2022
Tackling Provably Hard Representative Selection via Graph Neural Networks Seyed Mehran Kazemi Anton Tsitsulin Hossein Esfandiari M. Bateni Deepak Ramachandran Bryan Perozzi Vahab Mirrokni 22 2 0 20 May 2022
Effects of Graph Convolutions in Multi-layer Networks Aseem Baranwal K. Fountoulakis Aukosh Jagannath 13 23 0 20 Apr 2022
Augmentation-Free Graph Contrastive Learning with Performance Guarantee Haonan Wang Jieyu Zhang Qi Zhu Wei Huang 13 31 0 11 Apr 2022
Graph Attention Retrospective K. Fountoulakis Amit Levi Shenghao Yang Aseem Baranwal Aukosh Jagannath GNN 9 35 0 26 Feb 2022
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 14 96 0 16 Feb 2022
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction Eli Chien Wei-Cheng Chang Cho-Jui Hsieh Hsiang-Fu Yu Jiong Zhang O. Milenkovic Inderjit S Dhillon 150 130 0 29 Oct 2021