기초과학연구원 의생명수학그룹
This seminar examines how generative AI advances three foundational tasks in causality, treated as distinct, modular problems: (1) causal inference via intervention‑effect estimation, (2) causal graph analysis, and (3) detection …
In this talk, we discuss the paper "Homeostatic forces underlying the daily pattern of sleep propensity" by Vasili Kharchenko et al., SLEEP Advances, 2025. Abstract The mismatch between rising sleep …
In this talk, we discuss the paper "Quantifying interventional causality by knockoff operation" by Xinyan Zhang and Luonan Chen, Science Advances, 2025. Abstract Causal inference between measured variables is crucial …
In this talk, we discuss the paper "FilterNet: Harnessing Frequency Filters for Time Series Forecasting" by Kun Yi et al., NeurIPS, 2024. Abstract Given the ubiquitous presence of time series …
Abstract Many natural systems exhibit complex dynamics and are prone to sudden changes or ‘regime shifts’. At the same time, many of these systems are sparsely observed posing considerable challenges …