In vivo oriented modeling with consideration of intracellular crowding. - Noriko Hiroi; Keisuke Iba; Akito Tabira; Takahiro Okuhara; Takeshi Kubojima; Takumi Hiraiwa; Tetsuya J. Kobayashi; Kotaro Oka; Akira Funahashi (EMBC, 2013)

Information decoding in microscopic biological processes. - Tetsuya J. Kobayashi (EMBC, 2013)

Fitness Gain of Individually Sensed Information by Cells. - Tetsuya J. Kobayashi; Yuki Sughiyama (Entropy, 2019)

Lineage EM algorithm for inferring latent states from cellular lineage trees. - So Nakashima; Yuki Sughiyama; Tetsuya J. Kobayashi (Bioinform., 2020)

Forward and Backward Bellman Equations Improve the Efficiency of the EM Algorithm for DEC-POMDP. - Takehiro Tottori; Tetsuya J. Kobayashi (Entropy, 2021)

An explainable deep learning-based algorithm with an attention mechanism for predicting the live birth potential of mouse embryos. - Yuta Tokuoka; Takahiro G. Yamada; Daisuke Mashiko; Zenki Ikeda; Tetsuya J. Kobayashi; Kazuo Yamagata; Akira Funahashi (Artif. Intell. Medicine, 2022)

Mean-Field Control Approach to Decentralized Stochastic Control with Finite-Dimensional Memories. - Takehiro Tottori; Tetsuya J. Kobayashi (CoRR, 2022)

Information Geometry of Dynamics on Graphs and Hypergraphs. - Tetsuya J. Kobayashi; Dimitri Loutchko; Atsushi Kamimura; Shuhei A. Horiguchi; Yuki Sughiyama (CoRR, 2022)

Memory-Limited Partially Observable Stochastic Control and Its Mean-Field Control Approach. - Takehiro Tottori; Tetsuya J. Kobayashi (Entropy, 2022)

Mol-PECO: a deep learning model to predict human olfactory perception from molecular structures. - Mengji Zhang; Yusuke Hiki; Akira Funahashi; Tetsuya J. Kobayashi (CoRR, 2023)

Information geometric bound on general chemical reaction networks. - Tsuyoshi Mizohata; Tetsuya J. Kobayashi; Louis-S. Bouchard; Hideyuki Miyahara (CoRR, 2023)

Decentralized Stochastic Control with Finite-Dimensional Memories: A Memory Limitation Approach. - Takehiro Tottori; Tetsuya J. Kobayashi (Entropy, 2023)

Forward-Backward Sweep Method for the System of HJB-FP Equations in Memory-Limited Partially Observable Stochastic Control. - Takehiro Tottori; Tetsuya J. Kobayashi (Entropy, 2023)

Integrating GNN and Neural ODEs for Estimating Non-Reciprocal Two-Body Interactions in Mixed-Species Collective Motion. - Masahito Uwamichi; Simon K. Schnyder; Tetsuya J. Kobayashi; Satoshi Sawai (NeurIPS, 2024)

Cramer-Rao bound and absolute sensitivity in chemical reaction networks. - Dimitri Loutchko; Yuki Sughiyama; Tetsuya J. Kobayashi (CoRR, 2024)

Integrating GNN and Neural ODEs for Estimating Two-Body Interactions in Mixed-Species Collective Motion. - Masahito Uwamichi; Simon K. Schnyder; Tetsuya J. Kobayashi; Satoshi Sawai (CoRR, 2024)

Ancestral Reinforcement Learning: Unifying Zeroth-Order Optimization and Genetic Algorithms for Reinforcement Learning. - So Nakashima; Tetsuya J. Kobayashi (CoRR, 2024)

Optimal control of stochastic reaction networks with entropic control cost and emergence of mode-switching strategies. - Shuhei A. Horiguchi; Tetsuya J. Kobayashi (CoRR, 2024)