Uncertainty in Graph Neural Networks: A Survey

11 March 2024

Papers citing "Uncertainty in Graph Neural Networks: A Survey"

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Title
How Particle System Theory Enhances Hypergraph Message Passing Yixuan Ma Kai Yi Pietro Lio Shi Jin Yu Wang 10 0 0 24 May 2025
CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection Songran Bai Xiaolong Zheng D. Zeng 73 1 0 03 Apr 2025
Towards Anthropomorphic Conversational AI Part I: A Practical Framework Fei Wei Yaliang Li Bolin Ding 60 0 0 28 Feb 2025
Uncertainty-Aware Graph Structure Learning Shen Han Zhiyao Zhou Jiawei Chen Zhezheng Hao Sheng Zhou Gang Wang Yan Feng Chong Chen C. Wang 98 2 0 20 Feb 2025
BANGS: Game-Theoretic Node Selection for Graph Self-Training Fangxin Wang Kay Liu Sourav Medya Philip S. Yu SSL 64 2 0 12 Oct 2024
Conditional Shift-Robust Conformal Prediction for Graph Neural Network Akansha Agrawal UQCV 146 1 0 20 May 2024
Uncertainty Quantification on Graph Learning: A Survey Chao Chen Chenghua Guo Rui Xu Xiangwen Liao Xi Zhang Sihong Xie Hui Xiong Mohit Bansal AI4CE 44 1 0 23 Apr 2024
Multitask Active Learning for Graph Anomaly Detection Wenjing Chang Kay Liu Kaize Ding Philip S. Yu Jianjun Yu 103 8 0 24 Jan 2024
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation Kim-Celine Kahl Carsten T. Lüth M. Zenk Klaus Maier-Hein Paul F. Jaeger UQCV 77 17 0 16 Jan 2024
On the Temperature of Bayesian Graph Neural Networks for Conformal Prediction Seohyeon Cha Honggu Kang Joonhyuk Kang 51 3 0 17 Oct 2023
Deep Insights into Noisy Pseudo Labeling on Graph Data Botao Wang Jia Li Yang Liu Jiashun Cheng Yu Rong Wenjia Wang Fugee Tsung NoLa 68 9 0 02 Oct 2023
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation Mingxuan Ju Tong Zhao Wenhao Yu Neil Shah Yanfang Ye 61 15 0 01 Oct 2023
Learning on Graphs with Out-of-Distribution Nodes Yunho Song Donglin Wang OODD 34 41 0 13 Aug 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 48 9 0 20 Jun 2023
Explaining Predictive Uncertainty with Information Theoretic Shapley Values David S. Watson Joshua O'Hara Niek Tax Richard Mudd Ido Guy TDI FAtt 44 22 0 09 Jun 2023
Topology-Aware Uncertainty for Image Segmentation Saumya Gupta Yikai Zhang Xiaoling Hu Prateek Prasanna Chao Chen 58 28 0 09 Jun 2023
A Survey on Explainability of Graph Neural Networks Jaykumar Kakkad Jaspal Jannu Kartik Sharma Charu C. Aggarwal Sourav Medya 45 25 0 02 Jun 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks Kexin Huang Ying Jin Emmanuel Candès J. Leskovec 147 61 0 23 May 2023
Uncertainty Propagation in Node Classification Zhao Xu Carolin (Haas) Lawrence Ammar Shaker Raman Siarheyeu BDL UQCV 94 2 0 03 Apr 2023
Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks Qingyi Wang Shenhao Wang Dingyi Zhuang Haris N. Koutsopoulos Jinhua Zhao AI4TS 34 20 0 07 Mar 2023
Conformal Prediction for Network-Assisted Regression Robert Lunde Elizaveta Levina Ji Zhu 44 16 0 20 Feb 2023
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks Yan Scholten Jan Schuchardt Simon Geisler Aleksandar Bojchevski Stephan Günnemann AAML 48 16 0 05 Jan 2023
Distribution Free Prediction Sets for Node Classification J. Clarkson AI4CE 82 24 0 26 Nov 2022
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on Graphs Hans Hao-Hsun Hsu Yuesong Shen Daniel Cremers 52 7 0 27 Oct 2022
Unsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method Yihong Huang Liping Wang Fan Zhang Xuemin Lin 48 23 0 24 Oct 2022
What Makes Graph Neural Networks Miscalibrated? Hans Hao-Hsun Hsu Yuesong Shen Christian Tomani Daniel Cremers 70 38 0 12 Oct 2022
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks Jian Kang Qinghai Zhou Hanghang Tong UQCV 74 21 0 12 Oct 2022
Empowering Graph Representation Learning with Test-Time Graph Transformation Wei Jin Tong Zhao Jiayu Ding Yozen Liu Jiliang Tang Neil Shah OOD 124 62 0 07 Oct 2022
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks Dingyi Zhuang Shenhao Wang Haris N. Koutsopoulos Jinhua Zhao 51 35 0 11 Aug 2022
Uncertainty Quantification for Traffic Forecasting: A Unified Approach Weizhu Qian Dalin Zhang Yan Zhao Kai Zheng James Jianqiao Yu BDL AI4TS 52 23 0 11 Aug 2022
Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective Gleb Bazhenov Sergei Ivanov Maxim Panov Alexey Zaytsev Evgeny Burnaev UQCV 60 10 0 21 Jun 2022
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs Kay Liu Yingtong Dou Yue Zhao Xueying Ding Xiyang Hu ... Lichao Sun Jundong Li George H. Chen Zhihao Jia Philip S. Yu OOD 41 93 0 21 Jun 2022
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 65 117 0 16 Jun 2022
On Calibration of Graph Neural Networks for Node Classification Tong Liu Yushan Liu Marcel Hildebrandt Mitchell Joblin Hang Li Volker Tresp 69 11 0 03 Jun 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 67 27 0 20 May 2022
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks Sai Munikoti D. Agarwal Laya Das Balasubramaniam Natarajan BDL UD 49 13 0 20 May 2022
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning Bat-Sheva Einbinder Yaniv Romano Matteo Sesia Yanfei Zhou UQCV 84 50 0 12 May 2022
PyGOD: A Python Library for Graph Outlier Detection Kay Liu Yingtong Dou Xueying Ding Xiyang Hu Ruitong Zhang Hao Peng Kai Shu Philip S. Yu AI4TS 37 51 0 26 Apr 2022
Information Gain Propagation: a new way to Graph Active Learning with Soft Labels Wentao Zhang Yexin Wang Zhenbang You Meng Cao Ping Huang Jiulong Shan Zhi-Xin Yang Tengjiao Wang AAML 56 19 0 02 Mar 2022
Improving Generalization via Uncertainty Driven Perturbations Matteo Pagliardini Gilberto Manunza Martin Jaggi Michael I. Jordan Tatjana Chavdarova AAML AI4CE 39 4 0 11 Feb 2022
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift Hongrui Liu Binbin Hu Xiao Wang Chuan Shi Qing Cui Jun Zhou 140 55 0 27 Jan 2022
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels Yayong Li Jie Yin Ling-Hao Chen 47 33 0 20 Jan 2022
Reliable Graph Neural Networks for Drug Discovery Under Distributional Shift Kehang Han Balaji Lakshminarayanan J. Liu OOD GNN 36 33 0 25 Nov 2021
Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection Saswati Ray S. Lakdawala Mononito Goswami Chufan Gao BDL 21 4 0 15 Nov 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 71 83 0 26 Oct 2021
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration Xiao Wang Hongrui Liu Chuan Shi Cheng Yang UQCV 148 116 0 29 Sep 2021
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks Lucie Charlotte Magister Dmitry Kazhdan Vikash Singh Pietro Lio 56 48 0 25 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 167 1,136 0 07 Jul 2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting Dongxian Wu Liyao (Mars) Gao X. Xiong Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu AI4TS 62 69 0 25 May 2021
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs Li Sun Zhongbao Zhang Jiawei Zhang Feiyang Wang Hao Peng Sen Su Philip S. Yu BDL 43 73 0 06 Apr 2021