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JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional
  Networks

JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks

12 October 2022
Jian Kang
Qinghai Zhou
Hanghang Tong
    UQCV
ArXivPDFHTML

Papers citing "JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks"

15 / 15 papers shown
Title
Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
Hongliang Chi
Qiong Wu
Zhengyi Zhou
Yao Ma
TDI
AAML
65
0
0
23 Mar 2025
Uncertainty Quantification on Graph Learning: A Survey
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
Uncertainty in Graph Neural Networks: A Survey
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
Active Learning for Graphs with Noisy Structures
Active Learning for Graphs with Noisy Structures
Hongliang Chi
Cong Qi
Suhang Wang
Yao Ma
22
0
0
04 Feb 2024
Cross-Space Adaptive Filter: Integrating Graph Topology and Node
  Attributes for Alleviating the Over-smoothing Problem
Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem
Chen Huang
Haoyang Li
Yifan Zhang
Wenqiang Lei
Jiancheng Lv
17
0
0
26 Jan 2024
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph
  Neural Networks
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
Puja Trivedi
Mark Heimann
Rushil Anirudh
Danai Koutra
Jayaraman J. Thiagarajan
UQCV
24
4
0
07 Jan 2024
Data-centric Graph Learning: A Survey
Data-centric Graph Learning: A Survey
Jixi Liu
Deyu Bo
Cheng Yang
Haoran Dai
Qi Zhang
Yixin Xiao
Yufei Peng
Chuan Shi
GNN
16
19
0
08 Oct 2023
Towards Data-centric Graph Machine Learning: Review and Outlook
Towards Data-centric Graph Machine Learning: Review and Outlook
Xin Zheng
Yixin Liu
Zhifeng Bao
Meng Fang
Xia Hu
Alan Wee-Chung Liew
Shirui Pan
GNN
AI4CE
15
19
0
20 Sep 2023
Class-Imbalanced Graph Learning without Class Rebalancing
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
12
8
0
27 Aug 2023
Towards Reliable Rare Category Analysis on Graphs via Individual
  Calibration
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration
Longfeng Wu
Bowen Lei
Dongkuan Xu
Dawei Zhou
UQCV
CML
21
9
0
19 Jul 2023
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks
He Zhang
Xingliang Yuan
Shirui Pan
18
11
0
30 Jan 2023
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence
  Calibration
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration
Xiao Wang
Hongrui Liu
Chuan Shi
Cheng Yang
UQCV
93
113
0
29 Sep 2021
Uncertainty Aware Semi-Supervised Learning on Graph Data
Uncertainty Aware Semi-Supervised Learning on Graph Data
Xujiang Zhao
Feng Chen
Shu Hu
Jin-Hee Cho
UQCV
EDL
BDL
102
130
0
24 Oct 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
1