Research
Publications
Category
Research Area
Year
-
2021 World Robot Competition Service Robot Category Partner Robot Challenge: Second Place
T. Matsushima et al．
-
DORi: Discovering Object Relationships for Moment Localization of a Natural Language Query in a Video
Cristian Rodriguez-Opazo, Edison Marrese-Taylor, Basura Fernando, Hongdong Li and Stephen Gould
The IEEE Winter Conference on Applications of Computer Vision (WACV). January 2021
-
Pixyz: a framework for developing deep generative models
Tutorial on Deep Probabilistic Generative Models for Robotics (IROS2020)
-
Modeling Task Uncertainty for Safe Meta-imitation Learning
Tatsuya Matsushima, Naruya Kondo, Yusuke Iwasawa, Kaoru Nasuno, Yutaka Matsuo
Frontiers in Robotics and AI, Vol. 7, pp.189,(2020)
-
Gravity of Location-based Service: Analyzing the Effects for Mobility Pattern and Location Prediction
Keiichi Ochiai, Yusuke Fukazawa, Wataru Yamada, Hiroyuki Manabe, Yutaka Matsuo
Proceedings of the International AAAI Conference on Web and Social Media, 14(1), pp.476-487 (2020)
-
Revealing the computational meaning of neocortical interarea signals
Hiroshi Yamakawa
Frontiers in Computational Neuroscience, Vol.14, No.74 (2020)
-
Distinct mechanisms of over-representation of landmarks and rewards in the hippocampus
Masaaki Sato, Kotaro Mizuta, Tanvir Islam, Masako Kawano, Yukiko Sekine, Takashi Takekawa, Daniel Gomez-Dominguez, Alexander Schmidt, Fred Wolf, Karam Kim, Hiroshi Yamakawa, Masamichi Ohkura, Min Goo Lee, Tomoki Fukai, Junichi Nakai, Yasunori Hayashi
Cell Reports, (2020)
-
Neuro-SERKET:Development of Integrative Cognitive System Through the Composition of Deep Probabilistic Generative Models
Tadahiro Taniguchi, Tomoaki Nakamura, Masahiro Suzuki, Ryo Kuniyasu, Kaede Hayashi, Akira Taniguchi, Takato Horii & Takayuki Nagai, Neuro-SERKET
New Generation Computing, (2020)
-
Attentional Reinforcement Learning in the Brain
Hiroshi Yamakawa
New Generation Computing, doi:10.1007/s00354-019-00081-z, (2020)
-
JSAI2018 Excellence Award: “Improving Robustness to Long Action Sequences by Partitioning into Subtasks and Predicting Abstracted Actions in Instruction Following.”
篠田 一聡，竹澤 祐貴，鈴木 雅大，岩澤 有祐，松尾 豊