Model-Based Reinforcement Learning via Meta-Policy Optimization. - Ignasi Clavera; Jonas Rothfuss; John Schulman; Yasuhiro Fujita 001; Tamim Asfour; Pieter Abbeel (CoRL, 2018)

Clipped Action Policy Gradient. - Yasuhiro Fujita 001; Shin-ichi Maeda (ICML, 2018)

A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning. - Yoshihiro Nagano; Shoichiro Yamaguchi; Yasuhiro Fujita 001; Masanori Koyama (ICML, 2019)

A Differentiable Gaussian-like Distribution on Hyperbolic Space for Gradient-Based Learning. - Yoshihiro Nagano; Shoichiro Yamaguchi; Yasuhiro Fujita 001; Masanori Koyama (CoRR, 2019)

Learning Latent State Spaces for Planning through Reward Prediction. - Aaron J. Havens; Yi Ouyang; Prabhat Nagarajan; Yasuhiro Fujita 001 (CoRR, 2019)

Distributed Reinforcement Learning of Targeted Grasping with Active Vision for Mobile Manipulators. - Yasuhiro Fujita 001; Kota Uenishi; Avinash Ummadisingu; Prabhat Nagarajan; Shimpei Masuda; Mario Ynocente Castro (IROS, 2020)

ChainerRL: A Deep Reinforcement Learning Library. - Yasuhiro Fujita 001; Prabhat Nagarajan; Toshiki Kataoka; Takahiro Ishikawa (J. Mach. Learn. Res., 2021)

Surface-Aligned Neural Radiance Fields for Controllable 3D Human Synthesis. - Tianhan Xu; Yasuhiro Fujita 001; Eiichi Matsumoto (CVPR, 2022)

PLaMo-100B: A Ground-Up Language Model Designed for Japanese Proficiency. - Kenshin Abe; Kaizaburo Chubachi; Yasuhiro Fujita 001; Yuta Hirokawa; Kentaro Imajo; Toshiki Kataoka; Hiroyoshi Komatsu; Hiroaki Mikami; Tsuguo Mogami; Shogo Murai; Kosuke Nakago; Daisuke Nishino; et al. (CoRR, 2024)

Entropy Controllable Direct Preference Optimization. - Motoki Omura; Yasuhiro Fujita 001; Toshiki Kataoka (CoRR, 2024)