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    • Interaction-Based Disentanglement of Entities for Object-Centric World Models

      Akihiro Nakano, Masahiro Suzuki, Yutaka Matsuo.

      “InteractioInternational Conference on Learning Representations (ICLR2023)

    • Universal Approximation with Neural Networks on Function Spaces

      Wataru Kumagai, Akiyoshi Sannai, Makoto Kawano

      Journal of Experimental & Theoretical Artificial Intelligence.(2022)

    • Scene Interpretation Method using Transformer and Self-Supervised Learning

      小林 由弥 鈴木 雅大 松尾 豊

      第37巻2号 J-STAGE, (2022)

    • Generalized Decision Transformer for Offline Hindsight Infomation Matching

      Hiroki Furuta, Yutaka Matsuo, and Shixiang Shane Gu

      International Conference on Learning Representations 2022 (ICLR2022, Spotlight).

    • Improving the Robustness to Variations of Objects and Instructions with a Neuro-Symbolic Approach for Interactive Instruction Following

      Kazutoshi Shinoda, Yuki Takezawa, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo

      Workshop on Novel Ideas in Learning-to-Learn through Interaction, EMNLP 2021.

    •  Pixyz: a framework for developing deep generative models

      Tutorial on Deep Probabilistic Generative Models for Robotics (IROS2020)

    • 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

    • Pixyz: a framework for developing complex deep generative models

      Workshop on Deep Probabilistic Generative Models for Cognitive Architecture in Robotics (IROS2019)

    • JSAI2019 Student Incentive Award: “Generative Query Networks as Meta-Learning”

      谷口尚平, 岩澤有祐, 松尾豊(受賞者:谷口尚平)