Research

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研究業績

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研究領域

  • Fixing the train-test objective discrepancy: Iterative Image Inpainting for Unsupervised Anomaly Detection

    Hitoshi Nakanishi, Masahiro Suzuki, Yutaka Matuo.

    J-Stage in August Vol.30, (2022).

  • Hippocampal formation-inspired probabilistic generative model

    Taniguchi, A., Fukawa, A., & Yamakawa,H

    Neural Networks: The Official Journal of the International Neural Network Society.(2022)

  • A whole brain probabilistic generative model: Toward realizingcognitive architectures for developmental robots

    Taniguchi, T., Yamakawa, H., Nagai, T., Doya, K., Sakagami, M., Suzuki, M., Nakamura, T., & Taniguchi, A

    Neural Networks: The Official Journal of the International Neural Network Society.(2022)

  • Conveying Intention by Motions With Awareness of Information Asymmetry

    Fukuchi, Y., Osawa, M., Yamakawa, H., Takahashi, T., & Imai, M

    Frontiers in Robotics and AI, 9. (2022)

  • Universal Approximation with Neural Networks on Function Spaces

    Wataru Kumagai, Akiyoshi Sannai, Makoto Kawano

    Journal of Experimental & Theoretical Artificial Intelligence.(2022)

  • A survey of multimodal deep generative models

    Masahiro Suzuki, Yutaka Matsuo

    Advanced Robotics.(2022)

  • Transformerと自己教師あり学習を用いたシーン解釈手法の提案

    小林 由弥 鈴木 雅大 松尾 豊

    第37巻2号 J-STAGE, (2022)

  • LSTMモデルによる金融経済レポートの指数化

    山本裕樹, 落合桂一, 鈴木雅大, 松尾豊

    情報処理学会論文誌トランザクションデジタルプラクティス (2022)

  • Information-theoretic regularization for learning global features by sequential VAE

    Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo

    Mach Learn (2021)

  • The whole brain architecture approach: Accelerating the developmentof artificial general intelligence by referring to the brain

    Hiroshi Yamakawa

    Neural Networks (2021)