
Research
Publications
Category
Research Area
Year
-
Explaining Intelligent Agent’s Future Motionon Basis of Vocabulary Learning WithHuman Goal Inference
Fukuchi, Y., Osawa, M., Yamakawa, H., & Imai, M.
IEEE Access, 10, 54336–54347. (2022)
-
Predicting production indices using deep learning models with inter-industry trade structures
山本裕樹,落合桂一,鈴木雅大,松尾豊
情報処理学会論文誌, (2022).
-
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)
-
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)
-
Extracting Sentiment Indicators from Financial Reports by Using LSTM Model
Yuhki Yamamoto, Keiichi Ochiai, Masahiro Suzuki, Yutaka Matsuo
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)