Rchr
J-GLOBAL ID:202301000987173350
Update date: May. 16, 2024
Takeishi Naoya
タケイシ ナオヤ | Takeishi Naoya
Affiliation and department:
Job title:
Lecturer
Homepage URL (2):
https://ntake.jp/ja
,
https://ntake.jp
Research field (1):
Intelligent informatics
Research keywords (2):
machine learning
, dynamical systems
Research theme for competitive and other funds (3):
- 2020 - 2025 Development of advanced machine learning methods in cooperation with prior knowledge as simulators
- 2019 - 2021 Intelligent Sensor Data Analysis based on Cooperation of Knowledge Bases and Statistical Machine Learning
- 2015 - 2018 小惑星探査高効率化のための形状・運動自動推定および自動画像航法
Papers (37):
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João A. Candido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis. Mimicking Better by Matching the Approximate Action Distribution. Proceedings of the 41st International Conference on Machine Learning. 2024
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Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda. Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling. Neural Networks. 2024. 171. 40-52
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Estimating Counterfactual Treatment Outcomes Over Time in Complex Multiagent Scenarios. IEEE Transactions on Neural Networks and Learning Systems. 2024. 1-15
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Keisuke Fujii, Kazushi Tsutsui, Atom Scott, Hiroshi Nakahara, Naoya Takeishi, Yoshinobu Kawahara. Adaptive Action Supervision in Reinforcement Learning from Real-World Multi-Agent Demonstrations. Proceedings of the 16th International Conference on Agents and Artificial Intelligence. 2024. 27-39
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Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis. Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. Advances in Neural Information Processing Systems 36. 2023. 1082-1099
more...
Patents (2):
Lectures and oral presentations (42):
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機械学習と科学モデル
(第38回人工知能学会全国大会 2024)
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On incorporation of machine learning and scientific models
(The 46th Annual Meeting of the Japan Neuroscience Society 2023)
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力学系の機械学習における事前知識活用の方法
(第25回情報論的学習理論ワークショップ 2022)
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混合密度ネットワークを用いた消費電力量予測手法の開発
(令和4年 電気学会 電力・エネルギー部門大会 2022)
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Variational Autoencoder with Differentiable Physics Engine for Human Gait Analysis and Synthesis
(Deep Generative Models and Downstream Applications Workshop 2021)
more...
Education (3):
- 2015 - 2018 The University of Tokyo The Graduate School of Engineering Department of Aeronautics and Astronautics
- 2013 - 2015 The University of Tokyo The Graduate School of Engineering Department of Aeronautics and Astronautics
- 2009 - 2013 The University of Tokyo The Faculty of Engineering Department of Aeronautics and Astroronautics
Work history (5):
- 2023/08 - 現在 The University of Tokyo Department of Advanced Interdisciplinary Studies, The Graduate School of Engineering Lecturer
- 2023/07 - 2023/07 The University of Tokyo Department of Aeronautics and Astronautics, The Graduate School of Engineering Lecturer
- 2020/09 - 2023/06 University of Applied Sciences and Arts Western Switzerland Geneva School of Business Administration Collaborateur Scientifique
- 2018/04 - 2020/08 RIKEN Structured Learning Team, Center for Advanced Intelligence Project Postdoctoral Researcher
- 2015/03 - 2018/03 Japan Society for the Promotion of Science Research Fellowship DC1
Committee career (1):
- 2022/06 - 現在 The Japanese Society for Artificial Intelligence Editorial board member
Association Membership(s) (1):
The Japanese Society for Artificial Intelligence
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