기초과학연구원 의생명수학그룹
In this talk, we discuss the paper "Principled PCA separates signal from noise in omics count data" by Jay S. Stanley III et al., bioarxiv, 2025. Abstract Principal component analysis (PCA) …
본 발표는 삼성에서 개발 중인 디지털 헬스케어 기술을 소개합니다. 먼저, 삼성 갤럭시 웨어러블 센서의 기능과 활용 가능성을 설명하며, 웰니스 및 의료기기 서비스의 상품화 사례를 소개합니다. 또한, 삼성이 디지털 헬스케어를 통해 …
Digital health leverages information and communication technologies to transform healthcare, enabling diverse solutions for continuous health management. Among these, wearable-based digital health plays a key role by collecting, monitoring, and …
Abstract Recent emergence and re-emergence of infectious disease pathogens have caused major disruptions to our society, highlighting the importance of managing ongoing outbreaks and predicting future epidemics. In this talk, …
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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 "Modeling personalized heart rate response to exercise and environmental factors with wearables data" by Nazaret et al., npj digital medicine, 2023. Abstract Heart …
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 …
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 "N-BEATS: Neural basis expansion analysis for interpretable time series forecasting" by B. Oreshkin et al., ICLR, 2020. Abstract We focus on solving the …
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 …