Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification

26 October 2021

Stephan Günnemann

Papers citing "Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification"

50 / 57 papers shown

Title
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know Shireen Kudukkil Manchingal Fabio Cuzzolin 42 0 0 08 May 2025
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs Shenzhi Yang Bin Liang An Liu Lin Gui Xingkai Yao Xiaofang Zhang OODD 57 3 0 18 Apr 2025
Prior2Former -- Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation Sebastian Schmidt Julius Körner Dominik Fuchsgruber Stefano Gasperini F. Tombari Stephan Günnemann 26 0 0 07 Apr 2025
CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection Songran Bai Xiaolong Zheng D. Zeng 35 0 0 03 Apr 2025
Enhance GNNs with Reliable Confidence Estimation via Adversarial Calibration Learning Yilong Wang J. Zhang Tianxiang Zhao Suhang Wang AAML 37 0 0 23 Mar 2025
Evidential Uncertainty Probes for Graph Neural Networks Linlin Yu Kangshuo Li Pritom Kumar Saha Yifei Lou Feng Chen EDL UQCV 72 0 0 11 Mar 2025
G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition Yicong Dong Rundong He Guangyao Chen Wentao Zhang Zhongyi Han Jieming Shi Yilong Yin 43 0 0 01 Mar 2025
Structural Alignment Improves Graph Test-Time Adaptation Hans Hao-Hsun Hsu Shikun Liu Han Zhao Pan Li OOD TTA 55 0 0 25 Feb 2025
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs Yuhan Chen Yihong Luo Yifan Song Pengwen Dai Jing Tang Xiaochun Cao OODD 32 1 0 25 Feb 2025
Uncertainty-Aware Graph Structure Learning Shen Han Zhiyao Zhou Jiawei Chen Zhezheng Hao Sheng Zhou Gang Wang Yan Feng C. L. P. Chen C. Wang 38 1 0 20 Feb 2025
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation Danny Wang Ruihong Qiu Guangdong Bai Zi Huang 53 0 0 09 Feb 2025
Enhancing Trustworthiness of Graph Neural Networks with Rank-Based Conformal Training Ting Wang Zhixin Zhou Rui Luo 23 5 0 06 Jan 2025
CUQ-GNN: Committee-based Graph Uncertainty Quantification using Posterior Networks C. Damke Eyke Hüllermeier BDL 30 0 0 06 Sep 2024
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations Richard Bergna Sergio Calvo-Ordoñez Felix L. Opolka Pietro Liò Jose Miguel Hernandez-Lobato BDL 24 2 0 28 Aug 2024
RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation Junyu Chen Long Shi Badong Chen 16 0 0 14 Aug 2024
Cluster-Wide Task Slowdown Detection in Cloud System Feiyi Chen Yingying Zhang Lunting Fan Yuxuan Liang Guansong Pang Qingsong Wen Shuiguang Deng 19 1 0 08 Aug 2024
Learning Divergence Fields for Shift-Robust Graph Representations Qitian Wu Fan Nie Chenxiao Yang Junchi Yan OOD 41 1 0 07 Jun 2024
Linear Opinion Pooling for Uncertainty Quantification on Graphs C. Damke Eyke Hüllermeier 25 1 0 06 Jun 2024
Uncertainty for Active Learning on Graphs Dominik Fuchsgruber Tom Wollschlager Bertrand Charpentier Antonio Oroz Stephan Günnemann 23 10 0 02 May 2024
Uncertainty Quantification on Graph Learning: A Survey Chao Chen Chenghua Guo Rui Xu Xiangwen Liao Xi Zhang Sihong Xie Hui Xiong Philip S. Yu AI4CE 24 1 0 23 Apr 2024
Novel Node Category Detection Under Subpopulation Shift Hsing-Huan Chung Shravan Chaudhari Yoav Wald Xing Han Joydeep Ghosh 16 1 0 01 Apr 2024
Uplift Modeling Under Limited Supervision G. Panagopoulos Daniele Malitesta Fragkiskos D. Malliaros Jun Pang CML 25 0 0 28 Mar 2024
Uncertainty in Graph Neural Networks: A Survey Fangxin Wang Yuqing Liu Kay Liu Yibo Wang Sourav Medya Philip S. Yu AI4CE 40 8 0 11 Mar 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges Wei Ju Siyu Yi Yifan Wang Zhiping Xiao Zhengyan Mao ... Senzhang Wang Xinwang Liu Xiao Luo Philip S. Yu Ming Zhang AI4CE 34 36 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
Multitask Active Learning for Graph Anomaly Detection Wenjing Chang Kay Liu Kaize Ding Philip S. Yu Jianjun Yu 37 8 0 24 Jan 2024
GOODAT: Towards Test-time Graph Out-of-Distribution Detection Luzhi Wang Dongxiao He He Zhang Yixin Liu Wenjie Wang Shirui Pan Di Jin Tat-Seng Chua OODD OOD 18 10 0 10 Jan 2024
Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission Jianfeng He Linlin Yu Shuo Lei Chang-Tien Lu Feng Chen UQLM 17 7 0 15 Nov 2023
Improvements on Uncertainty Quantification for Node Classification via Distance-Based Regularization Russell Hart Linlin Yu Yifei Lou Feng Chen UQCV 11 4 0 10 Nov 2023
On the Temperature of Bayesian Graph Neural Networks for Conformal Prediction Seohyeon Cha Honggu Kang Joonhyuk Kang 11 3 0 17 Oct 2023
Class-Imbalanced Graph Learning without Class Rebalancing Zhining Liu Ruizhong Qiu Zhichen Zeng Hyunsik Yoo David Zhou Zhe Xu Yada Zhu Kommy Weldemariam Jingrui He Hanghang Tong AI4CE 10 8 0 27 Aug 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 11 9 0 20 Jun 2023
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing Ziyan Wang Hao Wang UQCV 9 0 0 11 Jun 2023
dugMatting: Decomposed-Uncertainty-Guided Matting Jiawei Wu Changqing Zhang Zuoyong Li H. Fu Xi Peng Joey Tianyi Zhou 17 5 0 02 Jun 2023
Calibrating Multimodal Learning Huanrong Zhang Changqing Zhang Bing Wu H. Fu Joey Tianyi Zhou Q. Hu 41 16 0 02 Jun 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks Kexin Huang Ying Jin Emmanuel Candès J. Leskovec 22 57 0 23 May 2023
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention Hongjun Wang Jiyuan Chen Lun Du Qiang Fu Shi Han Xuan Song CML GNN 15 3 0 22 May 2023
Uncertainty Propagation in Node Classification Zhao Xu Carolin (Haas) Lawrence Ammar Shaker Raman Siarheyeu BDL UQCV 26 2 0 03 Apr 2023
Training, Architecture, and Prior for Deterministic Uncertainty Methods Bertrand Charpentier Chenxiang Zhang Stephan Günnemann UQCV OOD AI4CE 21 6 0 10 Mar 2023
AMIGO: Sparse Multi-Modal Graph Transformer with Shared-Context Processing for Representation Learning of Giga-pixel Images Ramin Nakhli Puria Azadi Moghadam Haoyang Mi H. Farahani Alexander S. Baras B. Gilks A. Bashashati MedIm ViT 14 17 0 01 Mar 2023
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts Gleb Bazhenov Denis Kuznedelev A. Malinin Artem Babenko Liudmila Prokhorenkova OOD 6 3 0 27 Feb 2023
Energy-based Out-of-Distribution Detection for Graph Neural Networks Qitian Wu Yiting Chen Chenxiao Yang Junchi Yan OODD 14 56 0 06 Feb 2023
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets Tianjin Huang Tianlong Chen Meng Fang Vlado Menkovski Jiaxu Zhao ... Yulong Pei D. Mocanu Zhangyang Wang Mykola Pechenizkiy Shiwei Liu GNN 31 14 0 28 Nov 2022
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection Yixin Liu Kaize Ding Huan Liu Shirui Pan 19 52 0 08 Nov 2022
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on Graphs Hans Hao-Hsun Hsu Yuesong Shen Daniel Cremers 10 7 0 27 Oct 2022
What Makes Graph Neural Networks Miscalibrated? Hans Hao-Hsun Hsu Yuesong Shen Christian Tomani Daniel Cremers 17 36 0 12 Oct 2022
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks Jian Kang Qinghai Zhou Hanghang Tong UQCV 25 21 0 12 Oct 2022
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation Jun Zhuang M. Hasan 15 20 0 21 Aug 2022
Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective Gleb Bazhenov Sergei Ivanov Maxim Panov Alexey Zaytsev Evgeny Burnaev UQCV 15 9 0 21 Jun 2022
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning Bertrand Charpentier Ransalu Senanayake Mykel Kochenderfer Stephan Günnemann PER UD 37 23 0 03 Jun 2022