Mana Fujiwara

This paper introduces a machine-learning framework to estimate latent world-model dynamics from behavioral data and applies it to analyze insight-like shifts in mouse behavior.

This study develops a regeneration-selection strategy for apple x pear hybrids to enable genetic transformation and rapid flowering through over-expression of MdFT1.

This paper develops a continuous reinforcement learning framework to model anticipatory homeostatic regulation and demonstrates its application to thermoregulation and multi-variable physiological control.