Accurate Connection Strength Estimation Based on Variational Bayes for Detecting Synaptic Plasticity. - Takuya Isomura; Yutaro Ogawa; Kiyoshi Kotani; Yasuhiko Jimbo (Neural Comput., 2015)

Cultured Cortical Neurons Can Perform Blind Source Separation According to the Free-Energy Principle. - Takuya Isomura; Kiyoshi Kotani; Yasuhiko Jimbo (PLoS Comput. Biol., 2015)

Linking Neuromodulated Spike-Timing Dependent Plasticity with the Free-Energy Principle. - Takuya Isomura; Koji Sakai; Kiyoshi Kotani; Yasuhiko Jimbo (Neural Comput., 2016)

Neurogenesis Enhances Response Specificity to Spatial Pattern Stimulation in Hippocampal Cultures. - Yukimi Tanaka; Takuya Isomura; Kenta Shimba; Kiyoshi Kotani; Yasuhiko Jimbo (IEEE Trans. Biomed. Eng., 2017)

Objective and efficient inference for couplings in neuronal networks. - Yu Terada; Tomoyuki Obuchi; Takuya Isomura; Yoshiyuki Kabashima (NeurIPS, 2018)

A Measure of Information Available for Inference. - Takuya Isomura (Entropy, 2018)

Task-Related Synaptic Changes Localized to Small Neuronal Population in Recurrent Neural Network Cortical Models. - Satoshi Kuroki; Takuya Isomura (Frontiers Comput. Neurosci., 2018)

Computational cost for determining an approximate global minimum using the selection and crossover algorithm. - Takuya Isomura (CoRR, 2019)

Bayesian Filtering with Multiple Internal Models: Toward a Theory of Social Intelligence. - Takuya Isomura; Thomas Parr; Karl J. Friston (Neural Comput., 2019)

Reverse-Engineering Neural Networks to Characterize Their Cost Functions. - Takuya Isomura; Karl J. Friston (Neural Comput., 2020)

Inferring Neuronal Couplings From Spiking Data Using a Systematic Procedure With a Statistical Criterion. - Yu Terada; Tomoyuki Obuchi; Takuya Isomura; Yoshiyuki Kabashima (Neural Comput., 2020)

Quadratic speedup of global search using a biased crossover of two good solutions. - Takuya Isomura (CoRR, 2021)

Kalman filters as the steady-state solution of gradient descent on variational free energy. - Manuel Baltieri; Takuya Isomura (CoRR, 2021)

Dimensionality reduction to maximize prediction generalization capability. - Takuya Isomura; Taro Toyoizumi (Nat. Mach. Intell., 2021)

Publisher Correction: Dimensionality reduction to maximize prediction generalization capability. - Takuya Isomura; Taro Toyoizumi (Nat. Mach. Intell., 2021)

On the Achievability of Blind Source Separation for High-Dimensional Nonlinear Source Mixtures. - Takuya Isomura; Taro Toyoizumi (Neural Comput., 2021)

Active Inference and Intentional Behaviour. - Karl J. Friston; Tommaso Salvatori; Takuya Isomura; Alexander Tschantz; Alex B. Kiefer; Tim Verbelen; Magnus T. Koudahl; Aswin Paul; Thomas Parr; Adeel Razi; Brett J. Kagan; Christopher L. Buckley; et al. (CoRR, 2023)

Real-World Robot Control Based on Contrastive Deep Active Inference With Demonstrations. - Kentaro Fujii; Takuya Isomura; Shingo Murata (IEEE Access, 2024)

On Predictive Planning and Counterfactual Learning in Active Inference. - Aswin Paul; Takuya Isomura; Adeel Razi (Entropy, 2024)

Active Inference and Intentional Behavior. - Karl J. Friston; Tommaso Salvatori; Takuya Isomura; Alexander Tschantz; Alex B. Kiefer; Tim Verbelen; Magnus T. Koudahl; Aswin Paul; Thomas Parr; Adeel Razi; Brett J. Kagan; Christopher L. Buckley; et al. (Neural Comput., 2025)