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Causal Attention for Interpretable and Generalizable Graph
  Classification
v1v2 (latest)

Causal Attention for Interpretable and Generalizable Graph Classification

Knowledge Discovery and Data Mining (KDD), 2021
30 December 2021
Yongduo Sui
Xiang Wang
Jiancan Wu
Min Lin
Xiangnan He
Tat-Seng Chua
    CMLOOD
ArXiv (abs)PDFHTML

Papers citing "Causal Attention for Interpretable and Generalizable Graph Classification"

50 / 89 papers shown
Toward a benchmark for CTR prediction in online advertising: datasets, evaluation protocols and perspectivesElectronic Commerce Research (ECR), 2025
Shan Gao
Yanwu Yang
58
0
0
01 Dec 2025
Graph Data Augmentation with Contrastive Learning on Covariate Distribution Shift
Graph Data Augmentation with Contrastive Learning on Covariate Distribution Shift
Fanlong Zeng
Wensheng Gan
OOD
197
0
0
30 Nov 2025
PISA: Prioritized Invariant Subgraph Aggregation
PISA: Prioritized Invariant Subgraph Aggregation
Ali Ghasemi
F. Wani
Maria Sofia Bucarelli
Fabrizio Silvestri
OOD
122
0
0
27 Nov 2025
Neurocircuitry-Inspired Hierarchical Graph Causal Attention Networks for Explainable Depression Identification
Neurocircuitry-Inspired Hierarchical Graph Causal Attention Networks for Explainable Depression Identification
Weidao Chen
Yuxiao Yang
Yueming Wang
170
0
0
18 Nov 2025
Peeling Context from Cause for Multimodal Molecular Property Prediction
Peeling Context from Cause for Multimodal Molecular Property Prediction
Tao Li
Kaiyuan Hou
Tuan Vinh
Carl Yang
Monika Raj
121
0
0
10 Nov 2025
On Joint Regularization and Calibration in Deep Ensembles
On Joint Regularization and Calibration in Deep Ensembles
Laurits Fredsgaard
Mikkel N. Schmidt
UQCV
346
0
0
06 Nov 2025
Evolving Graph Learning for Out-of-Distribution Generalization in Non-stationary Environments
Evolving Graph Learning for Out-of-Distribution Generalization in Non-stationary EnvironmentsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
Qingyun Sun
Jiayi Luo
Haonan Yuan
Xingcheng Fu
Hao Peng
Jianxin Li
Philip S. Yu
206
0
0
04 Nov 2025
SoREX: Towards Self-Explainable Social Recommendation with Relevant Ego-Path Extraction
SoREX: Towards Self-Explainable Social Recommendation with Relevant Ego-Path Extraction
Hanze Guo
Yijun Ma
Xiao Zhou
193
1
0
30 Sep 2025
Towards Minimal Causal Representations for Human Multimodal Language Understanding
Towards Minimal Causal Representations for Human Multimodal Language Understanding
Menghua Jiang
Yuncheng Jiang
Haifeng Hu
Sijie Mai
155
1
0
26 Sep 2025
C$^2$MIL: Synchronizing Semantic and Topological Causalities in Multiple Instance Learning for Robust and Interpretable Survival Analysis
C2^22MIL: Synchronizing Semantic and Topological Causalities in Multiple Instance Learning for Robust and Interpretable Survival Analysis
M. Cen
Zhenfeng Zhuang
Yuzhe Zhang
Min Zeng
Baptiste Magnier
Lequan Yu
Hong Zhang
Liansheng Wang
122
0
0
24 Sep 2025
Influence Guided Context Selection for Effective Retrieval-Augmented Generation
Influence Guided Context Selection for Effective Retrieval-Augmented Generation
Jiale Deng
Yanyan Shen
Ziyuan Pei
Youmin Chen
Linpeng Huang
381
1
0
21 Sep 2025
Federated Recommender System with Data Valuation for E-commerce Platform
Federated Recommender System with Data Valuation for E-commerce PlatformExpert systems with applications (ESWA), 2025
Jongwon Park
Minku Kang
Wooseok Sim
Soyoung Lee
Hogun Park
FedML
157
1
0
14 Sep 2025
Towards Faithful Class-level Self-explainability in Graph Neural Networks by Subgraph Dependencies
Towards Faithful Class-level Self-explainability in Graph Neural Networks by Subgraph Dependencies
Fanzhen Liu
Xiaoxiao Ma
Jian Yang
A. Abuadbba
Kristen Moore
Surya Nepal
Cécile Paris
Quan Z. Sheng
Jia Wu
141
1
0
15 Aug 2025
Disentangling Bias by Modeling Intra- and Inter-modal Causal Attention for Multimodal Sentiment Analysis
Disentangling Bias by Modeling Intra- and Inter-modal Causal Attention for Multimodal Sentiment Analysis
Menghua Jiang
Yuxia Lin
Baoliang Chen
Haifeng Hu
Yuncheng Jiang
Sijie Mai
160
0
0
07 Aug 2025
Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports
Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports
S. Balachandar
Shuvom Sadhuka
Emma Pierson
Emma Pierson
Nikhil Garg
AI4TS
251
1
0
10 Jun 2025
Out-of-Distribution Graph Models Merging
Out-of-Distribution Graph Models Merging
Yidi Wang
Jiawei Gu
pei Xiaobing
Xubin Zheng
Xiao Luo
Pengyang Wang
Ziyue Qiao
MoMeOODD
366
0
0
04 Jun 2025
CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor
CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor
Han Ji
Yuqi Feng
Jiahao Fan
Yanan Sun
OODCML
235
0
0
04 Jun 2025
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural NetworksInternational Conference on Learning Representations (ICLR), 2025
Jie Yang
Yuwen Wang
Kaixuan Chen
Tongya Zheng
Yihe Zhou
Zhenbang Xiao
Ji Cao
Mingli Song
Shixuan Liu
AI4CE
307
3
0
01 May 2025
Causal invariant geographic network representations with feature and structural distribution shifts
Causal invariant geographic network representations with feature and structural distribution shiftsFuture generations computer systems (FGCS), 2025
Yuhan Wang
Silu He
Qinyao Luo
Hongyuan Yuan
Ling Zhao
Jiawei Zhu
Haifeng Li
OOD
311
9
0
25 Mar 2025
Unleashing the Power of Large Language Model for Denoising Recommendation
Unleashing the Power of Large Language Model for Denoising RecommendationThe Web Conference (WWW), 2025
Shuyao Wang
Zhi Zheng
Yongduo Sui
Hui Xiong
373
10
0
13 Feb 2025
A Unified Invariant Learning Framework for Graph Classification
A Unified Invariant Learning Framework for Graph ClassificationKnowledge Discovery and Data Mining (KDD), 2025
Yongduo Sui
Jie Sun
Shuyao Wang
Zemin Liu
Daixin Wang
Longfei Li
Xiang Wang
OOD
261
2
0
22 Jan 2025
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution GeneralizationIndustrial Conference on Data Mining (IDM), 2024
Song Wang
Xiaodong Yang
Rashidul Islam
Huiyuan Chen
Minghua Xu
Jundong Li
Yiwei Cai
OODD
431
4
0
07 Jan 2025
Causal-aware Graph Neural Architecture Search under Distribution Shifts
Causal-aware Graph Neural Architecture Search under Distribution Shifts
Peiwen Li
Xin Wang
Zeyang Zhang
Yi Qin
Ziwei Zhang
Jialong Wang
Yang Li
Wenwu Zhu
CMLOOD
334
7
0
31 Dec 2024
Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation
Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge DistillationNeural Networks (NN), 2024
Chengyu Li
Debo Cheng
Guixian Zhang
Yi Li
Shichao Zhang
380
1
0
30 Nov 2024
MLDGG: Meta-Learning for Domain Generalization on Graphs
MLDGG: Meta-Learning for Domain Generalization on GraphsKnowledge Discovery and Data Mining (KDD), 2024
Q. Tian
Chen Zhao
Minglai Shao
Wenjun Wang
Yujie Lin
Dong Li
OODAI4CE
369
2
0
19 Nov 2024
Graph Neural Networks for Financial Fraud Detection: A Review
Graph Neural Networks for Financial Fraud Detection: A Review
Dawei Cheng
Yao Zou
Sheng Xiang
Changjun Jiang
AI4TS
294
42
0
01 Nov 2024
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
Kexin Zhang
Shuhan Liu
Song Wang
Weili Shi
Chen Chen
Pan Li
Sheng Li
Jundong Li
Kaize Ding
OOD
423
11
0
25 Oct 2024
GDDA: Semantic OOD Detection on Graphs under Covariate Shift via
  Score-Based Diffusion Models
GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion ModelsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Zhixia He
Chen Zhao
Minglai Shao
Yujie Lin
Dong Li
Q. Tian
DiffM
170
7
0
23 Oct 2024
HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric
  Model Migration
HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric Model Migration
Weijian Chen
Shuibing He
Haoyang Qu
Xuechen Zhang
GNN
365
1
0
01 Sep 2024
CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph Reasoning
CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph Reasoning
Jinze Sun
Yongpan Sheng
Lirong He
Yongbin Qin
Ming Liu
Tao Jia
CML
299
3
0
15 Aug 2024
Multi-task Heterogeneous Graph Learning on Electronic Health Records
Multi-task Heterogeneous Graph Learning on Electronic Health RecordsNeural Networks (NN), 2024
Tsai Hor Chan
Guosheng Yin
Kyongtae Bae
Lequan Yu
CML
225
10
0
14 Aug 2024
Towards Few-shot Self-explaining Graph Neural Networks
Towards Few-shot Self-explaining Graph Neural Networks
Jingyu Peng
Qi Liu
Linan Yue
Zaixi Zhang
Kai Zhang
Yunhao Sha
MILM
186
4
0
14 Aug 2024
CROCODILE: Causality aids RObustness via COntrastive DIsentangled
  LEarning
CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning
Gianluca Carloni
Sotirios A. Tsaftaris
Sara Colantonio
OOD
230
2
0
09 Aug 2024
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
DIVE: Subgraph Disagreement for Graph Out-of-Distribution GeneralizationKnowledge Discovery and Data Mining (KDD), 2024
Xin Sun
Liang Wang
Qiang Liu
Shu Wu
Zilei Wang
Liang Wang
OODCML
297
11
0
08 Aug 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
Wenyu Mao
Jiancan Wu
Haoyang Liu
Yongduo Sui
Xiang Wang
OOD
451
6
0
03 Aug 2024
Unifying Invariant and Variant Features for Graph Out-of-Distribution
  via Probability of Necessity and Sufficiency
Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency
Xuexin Chen
Ruichu Cai
Kaitao Zheng
Zhifan Jiang
Zhengting Huang
Zhifeng Hao
Zijian Li
306
0
0
21 Jul 2024
Rethinking Fair Graph Neural Networks from Re-balancing
Rethinking Fair Graph Neural Networks from Re-balancing
Zhixun Li
Yushun Dong
Qiang Liu
Jeffrey Xu Yu
182
16
0
16 Jul 2024
Empowering Graph Invariance Learning with Deep Spurious Infomax
Empowering Graph Invariance Learning with Deep Spurious Infomax
Tianjun Yao
Yongqiang Chen
Zhenhao Chen
Kai Hu
Zhiqiang Shen
Kun Zhang
OOD
282
15
0
13 Jul 2024
Graph Neural Network Causal Explanation via Neural Causal Models
Graph Neural Network Causal Explanation via Neural Causal Models
Arman Behnam
Binghui Wang
CML
221
10
0
12 Jul 2024
Causal Inference with Latent Variables: Recent Advances and Future
  Prospectives
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
Yaochen Zhu
Yinhan He
Jing Ma
Mengxuan Hu
Sheng Li
Jundong Li
CML
300
7
0
20 Jun 2024
Teleporter Theory: A General and Simple Approach for Modeling
  Cross-World Counterfactual Causality
Teleporter Theory: A General and Simple Approach for Modeling Cross-World Counterfactual Causality
Jiangmeng Li
Bin Qin
Qirui Ji
Yi Li
Jingyao Wang
Jianwen Cao
Jianwei Niu
253
0
0
17 Jun 2024
How Interpretable Are Interpretable Graph Neural Networks?
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen
Yatao Bian
Bo Han
James Cheng
216
13
0
12 Jun 2024
SIG: Efficient Self-Interpretable Graph Neural Network for
  Continuous-time Dynamic Graphs
SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic Graphs
Lanting Fang
Yulian Yang
Kai Wang
Shanshan Feng
Kaiyu Feng
Jie Gui
Shuliang Wang
Yew-Soon Ong
235
2
0
29 May 2024
A Unified Temporal Knowledge Graph Reasoning Model Towards Interpolation
  and Extrapolation
A Unified Temporal Knowledge Graph Reasoning Model Towards Interpolation and Extrapolation
Kai Chen
Ye Wang
Yitong Li
Aiping Li
Han Yu
Xin Song
177
11
0
28 May 2024
Safety in Graph Machine Learning: Threats and Safeguards
Safety in Graph Machine Learning: Threats and Safeguards
Song Wang
Yushun Dong
Binchi Zhang
Zihan Chen
Xingbo Fu
Yinhan He
Cong Shen
Chuxu Zhang
Nitesh Chawla
Wenlin Yao
287
11
0
17 May 2024
Towards Robust Trajectory Representations: Isolating Environmental
  Confounders with Causal Learning
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
Kang Luo
Yuanshao Zhu
Wei Chen
Kun Wang
Zhengyang Zhou
Sijie Ruan
Yuxuan Liang
182
10
0
22 Apr 2024
Graphs Generalization under Distribution Shifts
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Qin Tian
Wenjun Wang
Chen Zhao
Minglai Shao
Wang Zhang
Dong Li
OOD
236
2
0
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CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for
  Spatiotemporal Time Series Imputation
CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series ImputationInternational Conference on Information and Knowledge Management (CIKM), 2024
Baoyu Jing
Dawei Zhou
Kan Ren
Carl Yang
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347
18
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Graph Neural Network with Two Uplift Estimators for Label-Scarcity
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Dingyuan Zhu
Daixin Wang
Qing Cui
Kun Kuang
Yan Zhang
Yulin Kang
Jun Zhou
169
3
0
11 Mar 2024
Cooperative Classification and Rationalization for Graph Generalization
Cooperative Classification and Rationalization for Graph GeneralizationThe Web Conference (WWW), 2024
Linan Yue
Qi Liu
Ye Liu
Weibo Gao
Fangzhou Yao
Wenfeng Li
235
12
0
10 Mar 2024
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