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A Survey of Trustworthy Graph Learning: Reliability, Explainability, and
  Privacy Protection

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection

20 May 2022
Bingzhe Wu
Jintang Li
Junchi Yu
Yatao Bian
Hengtong Zhang
Chaochao Chen
Chengbin Hou
Guoji Fu
Liang Chen
Tingyang Xu
Yu Rong
Xiaolin Zheng
Junzhou Huang
Ran He
Baoyuan Wu
Guangyu Sun
Peng Cui
Zibin Zheng
Zhe Liu
P. Zhao
    OOD
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Papers citing "A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection"

18 / 18 papers shown
Title
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
48
8
0
11 Mar 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise,
  Privacy and OOD Challenges
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
36
35
0
07 Mar 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies
  and An Outlook
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang
Hao Liu
Hui Xiong
CML
AI4CE
44
2
0
19 Dec 2023
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and
  Applications
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
Yi Zhang
Yuying Zhao
Zhaoqing Li
Xueqi Cheng
Yu-Chiang Frank Wang
Olivera Kotevska
Philip S. Yu
Tyler Derr
26
10
0
31 Aug 2023
Unstructured and structured data: Can we have the best of both worlds
  with large language models?
Unstructured and structured data: Can we have the best of both worlds with large language models?
W. Tan
18
1
0
25 Apr 2023
Mind the Label Shift of Augmentation-based Graph OOD Generalization
Mind the Label Shift of Augmentation-based Graph OOD Generalization
Junchi Yu
Jian Liang
R. He
34
27
0
27 Mar 2023
TopoImb: Toward Topology-level Imbalance in Learning from Graphs
TopoImb: Toward Topology-level Imbalance in Learning from Graphs
Tianxiang Zhao
Dongsheng Luo
Xiang Zhang
Suhang Wang
AI4CE
30
11
0
16 Dec 2022
Discovering Invariant Rationales for Graph Neural Networks
Discovering Invariant Rationales for Graph Neural Networks
Yingmin Wu
Xiang Wang
An Zhang
Xiangnan He
Tat-Seng Chua
OOD
AI4CE
99
224
0
30 Jan 2022
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
109
113
0
29 Sep 2021
Elastic Graph Neural Networks
Elastic Graph Neural Networks
Xiaorui Liu
W. Jin
Yao Ma
Yaxin Li
Hua Liu
Yiqi Wang
Ming Yan
Jiliang Tang
92
107
0
05 Jul 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
Ana Lucic
Maartje ter Hoeve
Gabriele Tolomei
Maarten de Rijke
Fabrizio Silvestri
112
142
0
05 Feb 2021
Membership Inference Attack on Graph Neural Networks
Membership Inference Attack on Graph Neural Networks
Iyiola E. Olatunji
Wolfgang Nejdl
Megha Khosla
AAML
38
97
0
17 Jan 2021
Explainability in Graph Neural Networks: A Taxonomic Survey
Explainability in Graph Neural Networks: A Taxonomic Survey
Hao Yuan
Haiyang Yu
Shurui Gui
Shuiwang Ji
167
592
0
31 Dec 2020
GraphFL: A Federated Learning Framework for Semi-Supervised Node
  Classification on Graphs
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
Binghui Wang
Ang Li
H. Li
Yiran Chen
85
115
0
08 Dec 2020
Model Extraction Attacks on Graph Neural Networks: Taxonomy and
  Realization
Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization
Bang Wu
Xiangwen Yang
Shirui Pan
Xingliang Yuan
MIACV
MLAU
52
53
0
24 Oct 2020
Stealing Links from Graph Neural Networks
Stealing Links from Graph Neural Networks
Xinlei He
Jinyuan Jia
Michael Backes
Neil Zhenqiang Gong
Yang Zhang
AAML
63
168
0
05 May 2020
CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal
  Cancer Histology Images
CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images
Yanning Zhou
S. Graham
Navid Alemi Koohbanani
Muhammad Shaban
Pheng-Ann Heng
Nasir M. Rajpoot
MedIm
27
173
0
03 Sep 2019
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
172
1,775
0
02 Mar 2017
1