기초과학연구원 의생명수학그룹
In this talk, we discuss the paper "Next generation reservoir computing", by Gauthier, et.al, Nat. Comm., 2021. Abstract : Reservoir computing is a best-in-class machine learning algorithm for processing information …
In this talk, we discuss the paper "SVD-AE: An asymmetric autoencoder with SVD regularization for multivariate time series anomaly detection" by Yueyue Yao, et.al., Neural Networks, 2024. Abstract Anomaly detection in …
Abstract: Malignant gliomas are highly invasive brain tumors. Recent attention has focused on their capacity for network-driven invasion, whereby mitotic events can be followed by the migration of nuclei along …
Title: Theoretical studies on biological oscillations by using waveform data and mathematical models Abstract: Temporal waveforms of biological oscillations are of various shapes. In our research, we have explored the functional implications of these waveform shapes. In particular, we theoretically showed that the period of circadian clocks is proportional to the waveform distortion from sinusoidal wave. It suggests that the circadian period can be stable against temperature changes only if the waveform becomes more distorted at higher temperatures. In this talk, I will explain my past research and discuss my future plans. Reference: Shingo Gibo, Gen Kurosawa, Non-sinusoidal Waveform in Temperature Compensated Circadian Oscillations, Biophysical Journal 116 (4) 741-751 (2019). doi: 10.1016/j.bpj.2018.12.022 Shingo Gibo, Gen Kurosawa, Theoretical study on the …
Abstract: Circadian clocks in cells and humans are heterogeneous in period and phase. This heterogeneity can be exploited not only to gain insight into the molecular basis of circadian rhythms, …
In this talk, we discuss the paper : "KAN: Kolmogorov-Arnold Networks," by Z Liu et al. Abstract: Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising …
In this talk, we study and discuss the paper "Laplacian renormalization group for heterogeneous networks" by Pablo Villegas et.al, Nature Physics, 2023. Abstract The renormalization group is the cornerstone of …
In this talk, we discuss the paper : “Solving Inverse Problems in Medical Imaging with Score-Based Generative Models” by Y Song et al. Reconstructing medical images from partial measurements is …
In this talk, we discuss the paper "cellFlow: a generative flow-based model for single-cell count data" by A. Palma et.al, ICLR, 2024. Abstract Generative modeling for single-cell RNA-seq has proven …
In this talk, we discuss the paper : “Diffusion Posterior Sampling for Linear Inverse Problem Solving- A Filtering Perspective” by Z. Dou& Y. Song Diffusion models have achieved tremendous success …
Abstract: In this talk, we propose novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms …
In this talk, we discuss the paper "Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model" by F. W. Townes et.al., Genome Biology, 2019. Abstract Single-cell …
