Uncertainty Aware Semi-Supervised Learning on Graph Data

24 October 2020

Papers citing "Uncertainty Aware Semi-Supervised Learning on Graph Data"

24 / 74 papers shown

Title
Energy-based Out-of-Distribution Detection for Graph Neural Networks Qitian Wu Yiting Chen Chenxiao Yang Junchi Yan OODD 27 57 0 06 Feb 2023
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection Yixin Liu Kaize Ding Huan Liu Shirui Pan 24 53 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 25 7 0 27 Oct 2022
What Makes Graph Neural Networks Miscalibrated? Hans Hao-Hsun Hsu Yuesong Shen Christian Tomani Daniel Cremers 32 36 0 12 Oct 2022
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks Jian Kang Qinghai Zhou Hanghang Tong UQCV 38 21 0 12 Oct 2022
Consistency-Based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification Shafa Balaram C. Nguyen Ashraf Kassim Pavitra Krishnaswamy EDL 10 11 0 05 Sep 2022
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation Jun Zhuang M. Hasan 36 20 0 21 Aug 2022
USB: A Unified Semi-supervised Learning Benchmark for Classification Yidong Wang Hao Chen Yue Fan Wangbin Sun R. Tao ... T. Shinozaki Bernt Schiele Jindong Wang Xingxu Xie Yue Zhang 27 113 0 12 Aug 2022
Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting Bohan Tang Yiqi Zhong Chenxin Xu Wei Wu Ulrich Neumann Yanfeng Wang Ya-Qin Zhang Siheng Chen 36 9 0 11 Jul 2022
Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective Gleb Bazhenov Sergei Ivanov Maxim Panov Alexey Zaytsev Evgeny Burnaev UQCV 33 9 0 21 Jun 2022
A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning Zhen Guo Zelin Wan Qisheng Zhang Xujiang Zhao F. Chen Jin-Hee Cho Qi Zhang Lance M. Kaplan Dong-Ho Jeong A. Jøsang UQCV EDL 17 10 0 12 Jun 2022
PseudoProp: Robust Pseudo-Label Generation for Semi-Supervised Object Detection in Autonomous Driving Systems Shu Hu Chunfang Liu Jayanta K. Dutta Ming-Ching Chang Siwei Lyu Naveen Ramakrishnan 13 15 0 11 Mar 2022
SEED: Sound Event Early Detection via Evidential Uncertainty Xujiang Zhao Xuchao Zhang Wei Cheng Wenchao Yu Yuncong Chen Haifeng Chen F. Chen EDL 32 11 0 05 Feb 2022
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 41 80 0 26 Oct 2021
Collaborative Uncertainty in Multi-Agent Trajectory Forecasting Bohan Tang Yiqi Zhong Ulrich Neumann G. Wang Ya-Qin Zhang Siheng Chen 13 24 0 26 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 48 48 0 06 Oct 2021
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration Xiao Wang Hongrui Liu Chuan Shi Cheng Yang UQCV 109 113 0 29 Sep 2021
Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions Xuefeng Du Tian Bian Yu Rong Bo Han Tongliang Liu Tingyang Xu Wenbing Huang Yixuan Li Junzhou Huang NoLa 38 11 0 14 Jun 2021
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future David Ahmedt-Aristizabal M. Armin Simon Denman Clinton Fookes L. Petersson 16 178 0 27 May 2021
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions Bertrand Charpentier Oliver Borchert Daniel Zügner Simon Geisler Stephan Günnemann UQCV BDL 27 17 0 10 May 2021
Graph-based Semi-supervised Learning: A Comprehensive Review Zixing Song Xiangli Yang Zenglin Xu Irwin King 84 191 0 26 Feb 2021
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? Anna-Kathrin Kopetzki Bertrand Charpentier Daniel Zügner Sandhya Giri Stephan Günnemann 23 45 0 28 Oct 2020
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 197 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015