Seunghan Lee
(B.S) Yonsei Univ., Business Administration/Applied Statistics
(M.S, Ph.D) Yonsei Univ., Statistics and Data Science
Research Topics
- Time Series (TS) Deep Learning
- TS Forecasting
- TS Representation Learning
- TS Diffusion Models, Foundation Models
T. 010-8768-8472
E. seunghan9613@yonsei.ac.kr
Recent Publications
- Partial Channel Dependence with Channel Masks for Time Series Foundation Models (NeurIPS Workshop 2024, Oral presentation)
- Sequential Order-Robust Mamba for Time Series Forecasting (NeurIPS Workshop 2024)
- ANT: Adaptive Noise Schedule for Time Series Diffusion Models (NeurIPS 2024)
- Soft Contrastive Learning for Time Series (ICLR 2024, Spotlight)
- Learning to Embed Time Series Patches Independently (ICLR 2024)
