Research
研究
研究業績
カテゴリー
研究領域
年
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Group Equivariant Conditional Neural Processes
Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, and Yutaka Matsuo.
International Conference on Learning Representations 2021 (ICLR2021).
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Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, and Shixiang Shane Gu.
International Conference on Learning Representations 2021 (ICLR2021).
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解剖学的構造から見える脳の計算機能
山川 宏
日本神経回路学会誌, 28(4), pp. 147–150, 2021. 3
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Variational Inference for Learning Representations of Natural Language Edits
Edison Marrese-Taylor, Machel Reid and Yutaka Matsuo.
The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21). February 2021.
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脳に学んだカノニカル知能機構の構築にむけて ―学習で得た知識を多面的に再利用する仕組みとは―
山川宏
認知モデル研究会, オンライン会議(日本標準時)
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2021年度 World Robot Competition Service Robot Category Partner Robot Challenge: 準優勝
松嶋 達也ほか
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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
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深層生成モデルと世界モデル
第13回汎用人工知能研究会
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Pixyz: a framework for developing deep generative models
Tutorial on Deep Probabilistic Generative Models for Robotics (IROS2020)
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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)