Welcome to my academic page!

I am a Ph.D. student at Xidian University, supervised by Prof. Bo Chen. My research focuses primarily on statistical machine learning, time series analysis, diffusion models, and related tasks. I also collaborate closely with Prof. Mingyuan Zhou from The University of Texas at Austin.

Research Interests

• Multivariate time series analysis: Tackling anomaly detection, probability prediction, and other challenges associated with high-dimensional non-stationary time series data.
• Image anomaly detection: Addressing anomaly detection problems for images in industrial settings.
• Optimal transport theory: Conditional transport, Embedding methods, Concept learning.
• Bayesian statistics: Deep generative model, Variational inference, Knowledge representation.

News

2024.06: Be invited to join the Program Committee for AAAI 2025.

2024.05: VPDM is accepted by ICML2024.

2024.01: TMDM is accepted by ICLR2024.

Publications

Yuxin Li, Yaoxuan Feng, Wenchao Chen, Yubiao Wang, Xinyue Hu, Baolin Sun, Chunhui Qu, Bo Chen*, and Mingyuan Zhou, Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection, to appear in International Conference on Machine Learning (ICML), Vienna, Austria, July 2024.

Yuxin Li,Wenchao Chen, Xinyue Hu, Bo Chen*, baolin sun, Mingyuan Zhou,Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting, to appear in International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024.

Yuxin Li, Wenchao Chen, Bo Chen, Dongsheng Wang, Long Tian and Mingyuan Zhou, Prototype-oriented Unsupervised Anomaly Detection for Multivariate Time Series, International Conference on Machine Learning (ICML), Hawaii, 2023.

Yuxin Li, Kunling He, Danlei Xu, Dingli Luo. A transfer learning method using speech data as the source domain for micro-Doppler classification tasks. Knowledge-Based Systems, 209, 106449.

Services

Conference Program Committee: AAAI.

Conference Reviewers: NeurIPS,ICML,ICLR,CVPR,AAAI,AISTATS.

Journal Reviewers: TNNLS.