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Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism
International Conference on Machine Learning (ICML), 2022
31 January 2022
Siqi Miao
Miaoyuan Liu
Pan Li
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Papers citing
"Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism"
32 / 82 papers shown
UGSL: A Unified Framework for Benchmarking Graph Structure Learning
Bahare Fatemi
Sami Abu-El-Haija
Anton Tsitsulin
Seyed Mehran Kazemi
Dustin Zelle
Neslihan Bulut
Jonathan J. Halcrow
Bryan Perozzi
262
11
0
21 Aug 2023
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning
The Web Conference (WWW), 2023
Yun Zhu
Haizhou Shi
Zhenshuo Zhang
Siliang Tang
464
14
0
24 Jul 2023
Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
Ling Yang
Jiayi Zheng
Heyuan Wang
Zhongyi Liu
Zhilin Huang
Shenda Hong
Wentao Zhang
Tengjiao Wang
243
21
0
28 Jun 2023
Structure-Sensitive Graph Dictionary Embedding for Graph Classification
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2023
Guangyi Liu
Tong Zhang
Xudong Wang
Wenting Zhao
Chuanwei Zhou
Zhen Cui
145
2
0
18 Jun 2023
Globally Interpretable Graph Learning via Distribution Matching
The Web Conference (WWW), 2023
Yi Nian
Yurui Chang
Wei Jin
Lu Lin
OOD
360
9
0
18 Jun 2023
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization
Xiner Li
Shurui Gui
Youzhi Luo
Shuiwang Ji
OODD
OOD
330
14
0
13 Jun 2023
Structural Re-weighting Improves Graph Domain Adaptation
International Conference on Machine Learning (ICML), 2023
Shikun Liu
Tianchun Li
Yongbin Feng
Nhan Tran
Haiying Zhao
Qiu Qiang
Pan Li
OOD
AI4CE
207
51
0
05 Jun 2023
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
Neural Information Processing Systems (NeurIPS), 2023
Owen Queen
Thomas Hartvigsen
Teddy Koker
Huan He
Theodoros Tsiligkaridis
Marinka Zitnik
AI4TS
308
34
0
03 Jun 2023
A Survey on Explainability of Graph Neural Networks
IEEE Data Engineering Bulletin (IEEE Data Eng. Bull.), 2023
Jaykumar Kakkad
Jaspal Jannu
Kartik Sharma
Charu C. Aggarwal
Sourav Medya
211
53
0
02 Jun 2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization
Kha-Dinh Luong
Mert Kosan
A. Silva
Ambuj K. Singh
264
6
0
25 May 2023
Conditional Graph Information Bottleneck for Molecular Relational Learning
International Conference on Machine Learning (ICML), 2023
Namkyeong Lee
Dongmin Hyun
Gyoung S. Na
Sungwon Kim
Junseok Lee
Chanyoung Park
249
34
0
29 Apr 2023
Unstructured and structured data: Can we have the best of both worlds with large language models?
IEEE Data Engineering Bulletin (IEEE Data Eng. Bull.), 2023
W. Tan
270
2
0
25 Apr 2023
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability
The European Symposium on Artificial Neural Networks (ESANN), 2023
Indro Spinelli
Michele Guerra
F. Bianchi
Simone Scardapane
190
1
0
14 Apr 2023
Counterfactual Learning on Graphs: A Survey
Machine Intelligence Research (MIR), 2023
Zhimeng Guo
Teng Xiao
Zongyu Wu
Charu C. Aggarwal
Hui Liu
Suhang Wang
CML
AI4CE
430
25
0
03 Apr 2023
Are More Layers Beneficial to Graph Transformers?
International Conference on Learning Representations (ICLR), 2023
Haiteng Zhao
Shuming Ma
Dongdong Zhang
Zhi-Hong Deng
Furu Wei
202
17
0
01 Mar 2023
Quantum Graph Learning: Frontiers and Outlook
Shuo Yu
Ciyuan Peng
Yingbo Wang
Ahsan Shehzad
Xiwei Xu
Edwin R. Hancock
AI4CE
191
9
0
02 Feb 2023
Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective
Hang Gao
Jiangmeng Li
Jingyao Wang
Hui Xiong
Xingzhe Su
Feng Wu
Changwen Zheng
Gang Hua
195
0
0
20 Jan 2023
CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis
Neural Networks (Neural Netw.), 2023
Kaizhong Zheng
Shujian Yu
Badong Chen
CML
412
58
0
04 Jan 2023
FAIR AI Models in High Energy Physics
Javier Mauricio Duarte
Haoyang Li
Avik Roy
Ruike Zhu
Eliu A. Huerta
...
Mark S. Neubauer
Sang Eon Park
M. Quinnan
R. Rusack
Zhizhen Zhao
320
13
0
09 Dec 2022
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift
Neural Information Processing Systems (NeurIPS), 2022
Yongduo Sui
Qitian Wu
Jiancan Wu
Daixin Wang
Longfei Li
An Zhang
Xiang Wang
Xiangnan He
OOD
311
49
0
05 Nov 2022
Interpretable Geometric Deep Learning via Learnable Randomness Injection
International Conference on Learning Representations (ICLR), 2022
Siqi Miao
Yunan Luo
Miaoyuan Liu
Pan Li
237
35
0
30 Oct 2022
Explaining the Explainers in Graph Neural Networks: a Comparative Study
ACM Computing Surveys (ACM CSUR), 2022
Antonio Longa
Steve Azzolin
G. Santin
G. Cencetti
Pietro Lio
Bruno Lepri
Baptiste Caramiaux
342
46
0
27 Oct 2022
Towards Prototype-Based Self-Explainable Graph Neural Network
ACM Transactions on Knowledge Discovery from Data (TKDD), 2022
Enyan Dai
Suhang Wang
192
18
0
05 Oct 2022
L2XGNN: Learning to Explain Graph Neural Networks
Machine-mediated learning (ML), 2022
G. Serra
Mathias Niepert
226
9
0
28 Sep 2022
Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks
Hyungeun Lee
Kijung Yoon
AI4CE
211
2
0
14 Sep 2022
Privacy and Transparency in Graph Machine Learning: A Unified Perspective
Megha Khosla
295
5
0
22 Jul 2022
FlowX: Towards Explainable Graph Neural Networks via Message Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Shurui Gui
Hao Yuan
Jie Wang
Qicheng Lao
Kang Li
Shuiwang Ji
316
24
0
26 Jun 2022
ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Jingwei Guo
Kaizhu Huang
Rui Zhang
Xinping Yi
AAML
309
17
0
27 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Proceedings of the IEEE (Proc. IEEE), 2022
He Zhang
Bang Wu
Lizhen Qu
Shirui Pan
Hanghang Tong
Jian Pei
373
150
0
16 May 2022
Graph Data Augmentation for Graph Machine Learning: A Survey
IEEE Data Engineering Bulletin (DEB), 2022
Tong Zhao
Wei Jin
Yozen Liu
Yingheng Wang
Gang Liu
Stephan Günnemann
Neil Shah
Meng Jiang
OOD
333
96
0
17 Feb 2022
Task-Agnostic Graph Explanations
Neural Information Processing Systems (NeurIPS), 2022
Yaochen Xie
S. Katariya
Xianfeng Tang
E-Wen Huang
Nikhil S. Rao
Karthik Subbian
Shuiwang Ji
221
32
0
16 Feb 2022
Out-Of-Distribution Generalization on Graphs: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Haoyang Li
Xin Eric Wang
Ziwei Zhang
Wenwu Zhu
OOD
CML
433
118
0
16 Feb 2022
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