Tianchun Wang

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 20

Top Topics

Feature Analysis

Pac Learnability

Information Bottleneck

Nonnegative Matrix Factorization

Top Venues

Publications

Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen
Explaining Time Series via Contrastive and Locally Sparse Perturbations. CoRR (2024)
Zhawnen Chen, Tianchun Wang, Yizhou Wang, Michal Kosinski, Xiang Zhang, Yun Fu, Sheng Li
Through the Theory of Mind's Eye: Reading Minds with Multimodal Video Large Language Models. CoRR (2024)
Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, Dongsheng Luo
Parametric Augmentation for Time Series Contrastive Learning. CoRR (2024)
Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks. ICLR (2024)
Zichuan Liu, Tianchun Wang, Jimeng Shi, Xu Zheng, Zhuomin Chen, Lei Song, Wenqian Dong, Jayantha Obeysekera, Farhad Shirani, Dongsheng Luo
TimeX++: Learning Time-Series Explanations with Information Bottleneck. CoRR (2024)
Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen
Explaining Time Series via Contrastive and Locally Sparse Perturbations. ICLR (2024)
Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, Dongsheng Luo
Parametric Augmentation for Time Series Contrastive Learning. ICLR (2024)
Xu Zheng, Farhad Shirani, Tianchun Wang, Shouwei Gao, Wenqian Dong, Wei Cheng, Dongsheng Luo
PAC Learnability under Explanation-Preserving Graph Perturbations. CoRR (2024)
Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian
Protecting Your LLMs with Information Bottleneck. CoRR (2024)
Xu Zheng, Tianchun Wang, Samin Yasar Chowdhury, Ruimin Sun, Dongsheng Luo
Unsafe Behavior Detection with Adaptive Contrastive Learning in Industrial Control Systems. EuroS&P Workshops (2023)
Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks. CoRR (2023)
Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen
GC-Flow: A Graph-Based Flow Network for Effective Clustering. ICML (2023)
Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang
DyExplainer: Explainable Dynamic Graph Neural Networks. CoRR (2023)
Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen
GC-Flow: A Graph-Based Flow Network for Effective Clustering. CoRR (2023)
Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, Xiang Zhang
Personalized Federated Learning via Heterogeneous Modular Networks. ICDM (2022)
Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Zhang
Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-Grained Air Quality. IEEE Trans. Knowl. Data Eng. 30 (12) (2018)
Tianchun Wang
Multi-Relevance Transfer Learning. CoRR (2017)
Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Zhang
Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-grained Air Quality. CoRR (2017)
Tengqi Ye, Tianchun Wang, Kevin McGuinness, Yu Guo, Cathal Gurrin
Learning Multiple Views with Orthogonal Denoising Autoencoders. MMM (1) (2016)
Tianchun Wang, Tengqi Ye, Cathal Gurrin
Transfer Nonnegative Matrix Factorization for Image Representation. MMM (2) (2016)
Tianchun Wang, Xiaoming Jin, Xuetao Ding, Xiaojun Ye
User Interests Imbalance Exploration in Social Recommendation: A Fitness Adaptation. CIKM (2014)