54 citations · 54 across the 2 of their papers we have counts for
2 papers
cs.AI2023
End-to-End Policy Gradient Method for POMDPs and Explainable Agents
Soichiro Nishimori, Sotetsu Koyamada, Shin Ishii
Real-world decision-making problems are often partially observable, and many can be formulated as a Partially Observable Markov Decision Process (POMDP). When we apply reinforcemen…
stat.ML2015★ 54 cited
Deep learning of fMRI big data: a novel approach to subject-transfer decoding
Sotetsu Koyamada, Yumi Shikauchi, Ken Nakae +2
As a technology to read brain states from measurable brain activities, brain decoding are widely applied in industries and medical sciences. In spite of high demands in these appli…