Publication

国内学会や国際会議での発表は学会発表のページにあります。

2025
武石 直也:
物理モデルと機械学習：深層学習時代の展開, 
化学工学, vol. 89, no. 9, pp. 445–458, 2025.
Koki Hirano, Naoya Takeishi, Takehisa Yairi:
Probabilistic Safety for Hard-to-Formalize Constraints via Conformal Neural CBFs, 
In Proceedings of the 64th IEEE Conference on Decision and Control, 2025. (to appear)
Akira Osaka, Naoya Takeishi, Takehisa Yairi:
Deterministic and Stochastic Hybrid Modeling with Regularization, 
In Proceedings of the 2025 IEEE International Conference on Systems, Man, and Cybernetics, 2025. (to appear)
Akira Osaka, Naoya Takeishi, Takehisa Yairi:
Domain Adaptation with Hybrid Modeling for Learning Dynamical Systems, 
In Proceedings of the 17th Asian Conference on Machine Learning, 2025. (to appear)
Haruki Matsuda, Yoshinori Matsuno, Takehisa Yairi:
Aircraft Weight Estimation Using Surveillance Data Based on Statistical Modeling of Climb-Thrust, 
Journal of Aircraft, 2025.
Osamu Yoshimatsu, Keiichirou Taguchi, Yoshihiro Sato, Takehisa Yairi:
Evaluating the Influence of Time Domain Feature Distributions on Estimating Rolling Bearing Flaking Size with Explainability, 
International Journal of Prognostics and Health Management, vol. 16, no. 3, 2025.
Andy Chung, Kumiko Tanaka-Ishii, Takehisa Yairi:
Portfolio selection based on market states acquired via price and non-price data, 
Discover Data, vol. 3, pp. 12, 2025.
Gengyu Li, Takehisa Yairi:
Semi-supervised domain adaptation with auxiliary task learning for RUL prediction, 
In Proceedings of 2025 IEEE International Conference on Prognostics and Health Management, 2025.
Haruki Matsuda, Naoya Takeishi, Takehisa Yairi:
High-Fidelity Aircraft Trajectory Generation Using a Flow-Based Generative Model, 
Transactions of the Japan Society for Aeronautical and Space Sciences, 2025. (in press)
Haruki Settai, Naoya Takeishi, Takehisa Yairi:
A Temporal Difference Method for Stochastic Continuous Dynamics, 
In Advances in Neural Information Processing Systems 38, 2025. (to appear)
2024
吉川 譲二, 滝本 憲弘, 武石 直也, 河原 吉伸, 船津 陽平:
蓄電池におけるグラフ深層学習による異常検知及び要因推定, 
電気学会論文誌Ｃ（電子・情報・システム部門誌）, vol. 114, 2024.
João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis:
Mimicking Better by Matching the Approximate Action Distribution, 
In Proceedings of the 41st International Conference on Machine Learning, pp. 5513-5532, 2024.
Christopher Aaron O'Hara, Takehisa Yairi:
Graph-based meta-learning for context-aware sensor management in nonlinear safety-critical environments, 
Advanced Robotics, vol. 38, no. 6, pp. 368-385, 2024.
Masanao Natsumeda, Takehisa Yairi:
Consistent Pretext and Auxiliary Tasks With Relative Remaining Useful Life Estimation, 
IEEE Transactions on Industrial Informatics, vol. 20, no. 4, pp. 6879-6888, 2024.
Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda:
Decentralized Policy Learning with Partial Observation and Mechanical Constraints for Multi-person Modeling, 
Neural Networks, vol. 171, pp. 40-52, 2024.
Keisuke Fujii, Kazushi Tsutsui, Atom Scott, Hiroshi Nakahara, Naoya Takeishi, Yoshinobu Kawahara:
Adaptive Action Supervision in Reinforcement Learning from Real-World Multi-Agent Demonstrations, 
In Proceedings of the 16th International Conference on Agents and Artificial Intelligence, pp. 27-39, 2024.
Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda:
Estimating Counterfactual Treatment Outcomes Over Time in Complex Multi-Agent Scenarios, 
IEEE Transactions on Neural Networks and Learning Systems, 2024.
2023
Wenyi Liu, Takehisa Yairi:
A unifying view of multivariate state space models for soft sensors in industrial processes, 
IEEE Access, vol. 12, pp. 5920-5932, 2023.
Masanao Natsumeda, Takehisa Yairi:
Feature Selection with Partial Autoencoding for Zero-Sample Fault Diagnosis, 
IEEE Transactions on Industrial Informatics, vol. 20, no. 2, pp. 2144-2153, 2023.
二木 浩司, 矢入 健久:
深層オートエンコーダと拡張カルマンフィルタの併用による物体画像列からの3次元回転運動推定, 
システム制御情報学会論文誌, vol. 37, no. 1, pp. 12-21, 2023.
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis:
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability, 
In Advances in Neural Information Processing Systems 36, pp. 1082-1099, 2023.
Naoya Takeishi, Yoshinobu Kawahara:
A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores, 
Transactions on Machine Learning Research, 2023.
Samir Khan, Takehisa Yairi, Seiji Tsutsumi, Shinichi Nakasuka:
A review of physics-based learning for system health management, 
Annual Reviews in Control, vol. 57, pp. 100932, 2023.
Ryota Yagi, Takehisa Yairi, Akira Iwasaki:
Navigating the Metaverse: UAV-Based Cross-View Geo-Localization in Virtual Worlds, 
In Proceedings of the 2023 Workshop on UAVs in Multimedia: Capturing the World from a New Perspective, pp. 13-17, 2023.
Ryosuke Takayama, Masanao Natsumeda, Takehisa Yairi:
A semi-supervised RUL prediction with likelihood-based pseudo labeling for suspension histories, 
In Proceedings of the 2023 IEEE International Conference on Prognostics and Health Management, pp. 296-303, 2023.
2022
Ryosuke Matsuo, Shinya Yasuda, Taichi Kumagai, Natsuhiko Sato, Hiroshi Yoshida, Takehisa Yairi:
Residual Reinforcement Learning for Logistics Cart Transportation, 
Advanced Robotics, vol. 36, no. 8, pp. 404-421, 2022.
X. Phong Nguyen, Hung Q. Cao, Khang V. T. Nguyen, Hung Nguyen, Takehisa Yairi:
SeCAM: Tightly Accelerate the Image Explanation via Region-Based Segmentation, 
IEICE Transactions on Information and Systems, vol. E105.D, no. 8, pp. 1401-1417, 2022.
X. Phong Nguyen, Tho H. Tran, Nguyen B. Pham, Dung N. Do, Takehisa Yairi:
Human Language Explanation for a Decision Making Agent via Automated Rationale Generation, 
IEEE Access, vol. 10, pp. 110727-110741, 2022.
Koji Minoda, Takehisa Yairi:
3D Human Pose Estimation in Weightless Environments Using a Fisheye Camera, 
In Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4100-4105, 2022.
Takahiro Hori, Takehisa Yairi:
Low-latency LiDAR semantic segmentation, 
In Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 9886-9891, 2022.
Osamu Yoshimatsu, Takehisa Yairi:
Impact Analysis of Evaluation Task Setting on a Public Dataset for Rolling Bearing Diagnostics Using Deep Learning, 
In Proceedings of the 2022 61st Annual Conference of the Society of Instrument and Control Engineers, pp. 728-733, 2022.
Wenyi Liu, Takehisa Yairi, Nana Tamai:
Feature selection for quality prediction under distribution shift, 
In Proceedings of the 2022 61st Annual Conference of the Society of Instrument and Control Engineers, pp. 548-552, 2022.
Ryosuke Takayama, Takehisa Yairi, Nana Tamai:
Nonstationary and Sparse Linear Regression for State Prediction of Artificial Systems, 
In Proceedings of the 2022 61st Annual Conference of the Society of Instrument and Control Engineers, pp. 553-558, 2022.
Samir Khan, Takehisa Yairi, Shinichi Nakasuka, Seiji Tsutsumi:
Reinforcement Learning-based Anomaly Detection for PHM applications, 
In 2022 IEEE Aerospace Conference (AERO), 2022.
2021
Takehisa Yairi, Yusuke Fukushima, Chun Fui Liew, Yuki Sakai, Yukihito Yamaguchi:
A Data-Driven Approach to Anomaly Detection and Health Monitoring for Artificial Satellites, 
In Proceedings of the 2nd World Congress on Condition Monitoring, pp. 129-141, 2021.
Koji Minoda, Fabian Schilling, Valentin Wüest, Dario Floreano, Takehisa Yairi:
VIODE: A Simulated Dataset to Address the Challenges of Visual-Inertial Odometry in Dynamic Environments, 
IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 1343-1350, 2021.
2020
Takaaki Tagawa, Yukihiro Tadokoro, Takehisa Yairi:
Interactive Anomaly Identification with Erroneous Feedback, 
International Journal of Prognostics and Health Management, vol. 11, no. 2, 2020.
Samir Khan, Takehisa Yairi:
Diagnosing Intermittent Faults through Non-linear Analysis, 
IFAC-PapersOnLine, vol. 53, no. 2, pp. 10304-10309, 2020.
Hidekazu Karino, Takehisa Yairi, Tetsujiro Ninomiya, Koichi Hori:
Estimating Aerodynamic Coefficients from Uncertain Data of D-SEND Aircraft with Gaussian Process Regression, 
Transactions of the Japan Society for Aeronautical and Space Sciences, vol. 63, no. 6, pp. 257-264, 2020.
Yoshiyuki Anzai, Takehisa Yairi, Naoya Takeishi, Yuichi Tsuda, Naoko Ogawa:
Visual localization for asteroid touchdown operation based on local image features, 
Astrodynamics, vol. 4, pp. 149-161, 2020.
Takaaki Tagawa, Yukihiro Tadokoro, Takehisa Yairi:
Scalable Change Analysis and Representation Using Characteristic Function, 
International Journal of Prognostics and Health Management, vol. 11, no. 1, 2020.
2019
Danielle M. DeLatte, Sarah T. Crites, Nicholas Guttenberg, Elizabeth J. Tasker, Takehisa Yairi:
Segmentation Convolutional Neural Networks for Automatic Crater Detection on Mars, 
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 9, pp. 2944-2957, 2019.
Danielle M. DeLatte, Sarah T. Crites, Nicholas Guttenberg, Takehisa Yairi:
Automated crater detection algorithms from a machine learning perspective in the convolutional neural network era, 
Advances in Space Research, vol. 64, no. 8, pp. 1615-1628, 2019.
Samir Khan, Chun Fui Liew, Takehisa Yairi, Richard McWilliam:
Unsupervised anomaly detection in unmanned aerial vehicles, 
Applied Soft Computing, vol. 83, pp. 105650, 2019.
矢入 健久:
機械学習とシステム同定：動的システム学習研究の動向, 
計測と制御, vol. 58, no. 3, pp. 176-181, 2019.
矢入 健久:
典型例で眺める機械学習の様々なタスク, 
ガスタービン学会誌, vol. 47, no. 5, pp. 282-287, 2019.
Riku Sasaki, Naoya Takeishi, Takehisa Yairi, Koichi Hori:
Neural Gray-Box Identification of Nonlinear Partial Differential Equations, 
In Proceedings the 16th Pacific Rim International Conference on Artificial Intelligence, pp. 309-321, 2019.
Ryo Sakagami, Naoya Takeishi, Takehisa Yairi, Koichi Hori:
Visualization Methods for Spacecraft Telemetry Data Using Change-point Detection and Clustering, 
Aerospace Technology Japan, vol. 17, no. 2, pp. 244-252, 2019.
2018
Samir Khan, Takehisa Yairi:
A review on the application of deep learning in system health management, 
Mechanical Systems and Signal Processing, vol. 107, pp. 241-265, 2018.
Rem Hida, Naoya Takeishi, Takehisa Yairi, Koichi Hori:
Dynamic and Static Topic Model for Analyzing Time-Series Document Collections, 
In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp. 516-520, 2018.
Naoya Takeishi, Takehisa Yairi, Yoshinobu Kawahara:
Factorially Switching Dynamic Mode Decomposition for Koopman Analysis of Time-Variant Systems, 
In 2018 IEEE Conference on Decision and Control, pp. 6402-6408, 2018.
2017
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi:
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition, 
In Advances in Neural Information Processing Systems 30, pp. 1130-1140, 2017.
Shinya Fujita, Takehisa Yairi, Koichi Hori, Shuhei Komatsu:
An Active Beacon-Based Target Localization Method for Unmanned Aerial Vehicles with Particle Filter, 
In Proceedings of the 2017 20th International Conference on Information Fusion, 2017.
Takehisa Yairi, Naoya Takeishi, Tetsuo Oda, Yuta Nakajima, Naoki Nishimura, Noboru Takata:
A Data-driven Health Monitoring Method for Satellite Housekeeping Data based on Probabilistic Clustering and Dimensionality Reduction, 
IEEE Transactions on Aerospace and Electronic Systems, vol. 53, no. 3, pp. 1384-1401, 2017.
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi:
Sparse Nonnegative Dynamic Mode Decomposition, 
In Proceedings of the 2017 IEEE International Conference on Image Processing, pp. 2682-2686, 2017.
Naoya Takeishi, Takehisa Yairi:
Visual Monocular Localization, Mapping, and Motion Estimation of a Rotating Small Celestial Body, 
Journal of Robotics and Mechatronics, vol. 29, no. 5, pp. 856-863, 2017.
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi:
Subspace dynamic mode decomposition for stochastic Koopman analysis, 
Physical Review E, vol. 96, no. 3, pp. 033310, 2017.
Naoya Takeishi, Yoshinobu Kawahara, Yasuo Tabei, Takehisa Yairi:
Bayesian Dynamic Mode Decomposition, 
In Proceedings of the 26th International Joint Conference on Artificial Intelligence, pp. 2814-2821, 2017.
2016
Naoya Takeishi, Takehisa Yairi:
Dynamic Grouped Mixture Models for Intermittent Multivariate Sensor Data, 
In Proceedings of the 20th Pacific Asia Conference on Knowledge Discovery and Data Mining, pp. 221-232, 2016.
Chun Fui Liew, Takehisa Yairi:
Robust Face Alignment with Random Forest: Analysis of Initialization, Landmarks Regression, and Shape Regularization Methods, 
IEICE Transaction on Information and Systems, vol. E99-D, no. 2, pp. 496-504, 2016.
2015
Naoya Takeishi, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu:
Simultaneous estimation of shape and motion of an asteroid for automatic navigation, 
In Proceedings of the 2015 IEEE International Conference on Robotics and Automation, pp. 2861-2866, 2015.
矢入 健久:
衛星の状態監視システムのつくりかた －過去のデータに基づく異常検知－, 
情報処理学会誌, vol. 56, no. 8, pp. 777-780, 2015.
Naoya Takeishi, Akira Tanimoto, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu:
Evaluation of Interest-Region Detectors and Descriptors for Automatic Landmark Tracking on Asteroids, 
Transactions of the Japan Society for Aeronautical and Space Sciences, vol. 58, no. 1, pp. 45-53, 2015.
Chun Fui Liew, Takehisa Yairi:
Facial Expression Recognition and Analysis: A Comparison Study of Feature Descriptors, 
IPSJ Transactions on Computer Vision and Applications, vol. 7, pp. 104-120, 2015.
桑原 絢一, 酒匂 信匡, 矢入 健久:
次元削減を用いた超小型衛星の画像劣化発生条件推定, 
日本航空宇宙学会論文集, vol. 63, no. 4, pp. 119-128, 2015.
Takehide Hirata, Yoshinobu Kawahara, Takehisa Yairi, Kazuya Asano, Ichiro Maeda, Toshihiro Sasaki, Kazuo Machida:
New monitoring technique for detecting buckling in the continuous annealing line using canonical correlation analysis, 
SICE Journal of Control, Measurement, and System Integration, vol. 8, no. 3, pp. 214-220, 2015.
Chun Fui Liew, Takehisa Yairi:
Designing a compact hexacopter with gimballed lidar and powerful onboard Linux computer, 
In Proceedings of the 2015 IEEE International Conference on Information and Automation, pp. 2523-2528, 2015.
Mayu Sakurada, Takehisa Yairi, Yuta Nakajima, Naoki Nishimura, Devi Parikh:
Semantic classification of spacecraft's status: integrating system intelligence and human knowledge, 
In Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing, pp. 81-84, 2015.
Takehide Hirata, Yoshinobu Kawahara, Takehisa Yairi, Kazuya Asano, Ichiro Maeda, Toshihiro Sasaki, Kazuo Machida:
New monitoring technique for detecting buckling in the continuous annealing line using canonical correlation analysis, 
SICE Journal of Control, Measurement, and System Integration, vol. 8, no. 3, pp. 214-220, 2015.