Olive Cawiding, Predicting multiple observations in complex systems through low-dimensional embeddings

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk, we discuss the paper, "Predicting multiple observations in complex systems through low-dimensional embeddings", by Tao Wu et. al., Nature Communications, 2024. Zoom : https://us06web.zoom.us/j/99567630778?pwd=N2ZrUWtqZzJ0YURVTzlZT3JJR3FUQT09 Abstract Forecasting all components

Hyun Kim, Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk, we discuss the paper "Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage" by Zhiwei Huang, et. al., bioRxiv,

Latent space dynamics identification – Youngsoo Choi

ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium) (pw: 1234)

Abstravt: Latent space dynamics identification (LaSDI) is an interpretable data-driven framework that follows three distinct steps, i.e., compression, dynamics identification, and prediction. Compression allows high-dimensional data to be reduced so

IBS 의생명수학그룹 Biomedical Mathematics Group
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IBS Biomedical Mathematics Group (BIMAG)
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