기초과학연구원 의생명수학그룹
In this talk, we discuss the paper "Causal disentanglement for single-cell representations and controllable counterfactual generation" by Yicheng Gao et al., Nature Communications, 2025. Abstract Conducting disentanglement learning on single-cell …
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 …
Classical machine learning models are typically trained under the assumption that the training (source) and test (target) data are drawn from the same distribution. However, real-world data are rarely clean …
Recent advances in data science have expanded the scope of data analysis beyond prediction accuracy toward interpretability, causal understanding, and generalizable learning across complex data structures. This lecture introduces three …
TBA