기초과학연구원 의생명수학그룹
In this talk, we discuss the paper "Machine learning methods trained on simple models can predict critical transitions in complex natural systems" by Smita Deb, Sahil Sidheekh, Christopher F. Clements, …
In this talk, we discuss the paper "Optimal transport for generating transition states in chemical reactions" by C. Duan et.al., Nat. Machine. Intelligence, 2025. Abstract Transition states (TSs) are transient …
In this talk, we discuss the paper "scGPT: toward building a foundation model for single-cell multi-omics using generative AI" by Haotian Cui, et.al. Nature Methods, 2024. Abstract Generative pretrained models …
Abstract: Weight calibration is a popular technique in handling covariate-shift problem in causal inference. It can be viewed as a dual optimization problem for incorporating the implicit regression model. We introduce the generalized entropy calibration as a general tool for weight calibration. Several interesting applications will be introduced in the context of causal inference. Furthermore, weight calibration can be used to transfer learning, which combines information from two different samples, one for source data and the other for target data.
In this talk, we discuss the paper "Effective Markovian dynamics method of solving non-Markovian dynamics of stochastic gene expression" by Youming Li and Chen Jia, Physical Review Letters, to appear. …
In this talk, we discuss the paper "Quantifying the energy landscape of high-dimensional oscillatory systems by diffusion decomposition" by S. Bian et.al., Cell Reports Physical Science, 2025. Abstract High-dimensional networks …
Abstract Topological Data Analysis (TDA) has emerged as a powerful framework for uncovering meaningful structure in high-dimensional, complex datasets. In this talk, we present two applications of TDA in analyzing patterns, one in …
In this talk, we discuss the paper "Circadian rhythm analysis using wearable-based accelerometry as a digital biomarker of aging and healthspan" by J. Shim et.al., npj digital medicine, 2024. Abstract …
In this talk, we discuss the paper "Statistical method scDEED for detecting dubious 2D single-cell embeddings and optimizing t-SNE and UMAP hyperparameters" by L. Xia et.al. Nature Communications, 2024. Abstract …
In this talk, we discuss the paper "Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains" by K. Lee. Abstract The ability of deep networks to learn superior …
Abstract The creation and inference of mathematical models is central to modern scientific discovery in the life sciences. As more realism is demanded of models, however, the conventional framework of …
In this talk, we discuss the paper "Physics-constrained neural ordinary differential equation models to discover and predict microbial community dynamics" by J. Thompson et al., bioarxiv, 2025. Abstract Microbial communities …