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Tianchun Wang

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Parametric Augmentation for Time Series Contrastive Learning

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Feb 16, 2024
Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, Dongsheng Luo

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PAC Learnability under Explanation-Preserving Graph Perturbations

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Feb 07, 2024
Xu Zheng, Farhad Shirani, Tianchun Wang, Shouwei Gao, Wenqian Dong, Wei Cheng, Dongsheng Luo

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Explaining Time Series via Contrastive and Locally Sparse Perturbations

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Jan 29, 2024
Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen

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DyExplainer: Explainable Dynamic Graph Neural Networks

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Oct 25, 2023
Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang

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Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks

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Oct 03, 2023
Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo

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GC-Flow: A Graph-Based Flow Network for Effective Clustering

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May 26, 2023
Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen

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Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-grained Air Quality

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Apr 11, 2018
Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei, Zhang

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Multi-Relevance Transfer Learning

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Nov 09, 2017
Tianchun Wang

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