Research
研究
研究業績
カテゴリー
研究領域
年
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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).
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Hippocampal formation-inspired probabilistic generative model
Taniguchi, A., Fukawa, A., & Yamakawa,H
Neural Networks: The Official Journal of the International Neural Network Society.(2022)
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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)
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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)
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Universal Approximation with Neural Networks on Function Spaces
Wataru Kumagai, Akiyoshi Sannai, Makoto Kawano
Journal of Experimental & Theoretical Artificial Intelligence.(2022)
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A survey of multimodal deep generative models
Masahiro Suzuki, Yutaka Matsuo
Advanced Robotics.(2022)
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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)
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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)
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“Information-theoretic regularization for learning global features by sequential VAE”
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo
Mach Learn (2021)
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The whole brain architecture approach: Accelerating the developmentof artificial general intelligence by referring to the brain
Hiroshi Yamakawa
Neural Networks (2021)