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Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning
  Attacks

Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks

30 September 2020
U. Shanthamallu
Jayaraman J. Thiagarajan
A. Spanias
    AAML
ArXivPDFHTML

Papers citing "Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks"

5 / 5 papers shown
Title
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
L. J. L. Lopez
Shaza Elsharief
Dhiyaa Al Jorf
Firas Darwish
Congbo Ma
Farah E. Shamout
38
0
0
04 May 2025
Hierarchical Uncertainty-Aware Graph Neural Network
Hierarchical Uncertainty-Aware Graph Neural Network
Yoonhyuk Choi
Jiho Choi
Taewook Ko
Chong-Kwon Kim
66
0
0
28 Apr 2025
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
46
8
0
11 Mar 2024
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph
  Neural Networks
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang
Da Zheng
Zihao Ye
Quan Gan
Mufei Li
...
J. Zhao
Haotong Zhang
Alex Smola
Jinyang Li
Zheng-Wei Zhang
AI4CE
GNN
184
731
0
03 Sep 2019
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