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An Zhang
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Year
Disentangled graph collaborative filtering
X Wang, H Jin, A Zhang, X He, T Xu, TS Chua
Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020
4802020
Discovering invariant rationales for graph neural networks
YX Wu, X Wang, A Zhang, X He, TS Chua
arXiv preprint arXiv:2201.12872, 2022
2112022
Let invariant rationale discovery inspire graph contrastive learning
S Li, X Wang, A Zhang, Y Wu, X He, TS Chua
International conference on machine learning, 13052-13065, 2022
932022
Towards multi-grained explainability for graph neural networks
X Wang, Y Wu, A Zhang, X He, TS Chua
Advances in Neural Information Processing Systems 34, 18446-18458, 2021
752021
Crosscbr: Cross-view contrastive learning for bundle recommendation
Y Ma, Y He, A Zhang, X Wang, TS Chua
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
652022
On generative agents in recommendation
A Zhang, Y Chen, L Sheng, X Wang, TS Chua
Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024
432024
Reinforced causal explainer for graph neural networks
X Wang, Y Wu, A Zhang, F Feng, X He, TS Chua
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 2297-2309, 2022
432022
Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering
A Zhang, W Ma, X Wang, TS Chua
Thirty-sixth Conference on Neural Information Processing Systems, 2022
422022
Invariant Collaborative Filtering to Popularity Distribution Shift
A Zhang, J Zheng, X Wang, Y Yuan, TS ChuI
arXiv preprint arXiv:2302.05328, 2023
292023
Large language model can interpret latent space of sequential recommender
Z Yang, J Wu, Y Luo, J Zhang, Y Yuan, A Zhang, X Wang, X He
arXiv preprint arXiv:2310.20487, 2023
242023
Cooperative explanations of graph neural networks
J Fang, X Wang, A Zhang, Z Liu, X He, TS Chua
Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023
222023
Causal screening to interpret graph neural networks
X Wang, Y Wu, A Zhang, X He, T Chua
19*2021
Evaluating post-hoc explanations for graph neural networks via robustness analysis
J Fang, W Liu, Y Gao, Z Liu, A Zhang, X Wang, X He
Advances in Neural Information Processing Systems 36, 2024
172024
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting
A Zhang, F Liu, W Ma, Z Cai, X Wang, T Chua
Eleventh International Conference on Learning Representations, 2023
142023
Deconfounding to explanation evaluation in graph neural networks
YX Wu, X Wang, A Zhang, X Hu, F Feng, X He, TS Chua
arXiv preprint arXiv:2201.08802, 2022
142022
Relm: Leveraging language models for enhanced chemical reaction prediction
Y Shi, A Zhang, E Zhang, Z Liu, X Wang
arXiv preprint arXiv:2310.13590, 2023
132023
Adversarial causal augmentation for graph covariate shift
Y Sui, X Wang, J Wu, A Zhang, X He
arXiv preprint arXiv:2211.02843, 2022
102022
Empowering collaborative filtering with principled adversarial contrastive loss
A Zhang, L Sheng, Z Cai, X Wang, TS Chua
Advances in Neural Information Processing Systems 36, 2024
92024
On regularization for explaining graph neural networks: An information theory perspective
J Fang, G Zhang, K Wang, W Du, Y Duan, Y Wu, R Zimmermann, X Chu, ...
IEEE Transactions on Knowledge and Data Engineering, 2024
82024
Online distillation-enhanced multi-modal transformer for sequential recommendation
W Ji, X Liu, A Zhang, Y Wei, Y Ni, X Wang
Proceedings of the 31st ACM International Conference on Multimedia, 955-965, 2023
82023
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Articles 1–20