Publication
2024
João A. Cândido Ramos; Lionel Blondé; Naoya Takeishi; Alexandros Kalousis
Mimicking Better by Matching the Approximate Action Distribution Proceedings Article
In: Proceedings of the 41st International Conference on Machine Learning, pp. 5513-5532, 2024.
@inproceedings{ramosMimickingBetterMatching2024,
title = {Mimicking Better by Matching the Approximate Action Distribution},
author = {João A. Cândido Ramos and Lionel Blondé and Naoya Takeishi and Alexandros Kalousis},
url = {https://proceedings.mlr.press/v235/candido-ramos24a.html},
year = {2024},
date = {2024-07-21},
urldate = {2024-07-21},
booktitle = {Proceedings of the 41st International Conference on Machine Learning},
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Naoya Takeishi
Toward Bayesian Deep Grey-box Modeling Conference
International Conference on Scientific Computing and Machine Learning, Kyoto, 2024.
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year = {2024},
date = {2024-03-19},
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Christopher Aaron O'Hara; Takehisa Yairi
Graph-based meta-learning for context-aware sensor management in nonlinear safety-critical environments Journal Article
In: Advanced Robotics, vol. 38, no. 6, pp. 368–385, 2024.
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doi = {10.1080/01691864.2024.2327083},
year = {2024},
date = {2024-03-12},
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journal = {Advanced Robotics},
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Masanao Natsumeda; Takehisa Yairi
Consistent Pretext and Auxiliary Tasks With Relative Remaining Useful Life Estimation Journal Article
In: IEEE Transactions on Industrial Informatics, vol. 20, no. 4, pp. 6879-6888, 2024.
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author = {Masanao Natsumeda and Takehisa Yairi},
doi = {10.1109/TII.2024.3353923},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-26},
journal = {IEEE Transactions on Industrial Informatics},
volume = {20},
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Keisuke Fujii; Koh Takeuchi; Atsushi Kuribayashi; Naoya Takeishi; Yoshinobu Kawahara; Kazuya Takeda
Estimating Counterfactual Treatment Outcomes Over Time in Complex Multi-Agent Scenarios Journal Article
In: IEEE Transactions on Neural Networks and Learning Systems, 2024.
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doi = {10.1109/TNNLS.2024.3361166},
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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 Article
In: Proceedings of the 16th International Conference on Agents and Artificial Intelligence, pp. 27–39, 2024.
@inproceedings{fujiiAdaptiveActionSupervision2024,
title = {Adaptive Action Supervision in Reinforcement Learning from Real-World Multi-Agent Demonstrations},
author = {Keisuke Fujii and Kazushi Tsutsui and Atom Scott and Hiroshi Nakahara and Naoya Takeishi and Yoshinobu Kawahara},
url = {https://arxiv.org/abs/2305.13030},
year = {2024},
date = {2024-01-01},
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Keisuke Fujii; Naoya Takeishi; Yoshinobu Kawahara; Kazuya Takeda
Decentralized Policy Learning with Partial Observation and Mechanical Constraints for Multi-person Modeling Journal Article
In: Neural Networks, vol. 171, pp. 40–52, 2024.
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2023
Osamu Yoshimatsu; Keiichiro Taguchi; Sato Yoshihiro; Takehisa Yairi
Size Estimation of Flaking in Rolling Bearings Using Deep Learning with Explainability Conference
Asia Pacific Conference of the Prognostics and Health Management Society, Tokyo, 2023.
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date = {2023-09-01},
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Ryo Sakurai; Takehisa Yairi
Proposal of a Time Series Anomaly Detection Method Using Image Encoding Techniques Conference
Asia Pacific Conference of the Prognostics and Health Management Society, Tokyo, 2023.
@conference{sakurai2023,
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Yutaka Watanabe; Takehisa Yairi
Application of Model-based Deep Reinforcement Learning Framework to Thermal Power Plant Operation Considering Performance Change Conference
Asia Pacific Conference of the Prognostics and Health Management Society, Tokyo, 2023.
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Wenyi Liu; Takehisa Yairi
Online fault detection for industrial processes through Kalman filter Conference
Asia Pacific Conference of the Prognostics and Health Management Society, Tokyo, 2023.
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Takuto Nakashima; Takehisa Yairi
Assessing the Performance of Transformer for Time Series Anomaly Detection Conference
Asia Pacific Conference of the Prognostics and Health Management Society, Tokyo, 2023.
@conference{nakashima2023,
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Wenyi Liu; Takehisa Yairi
A unifying view of multivariate state space models for soft sensors in industrial processes Journal Article
In: IEEE Access, vol. 12, pp. 5920–5932, 2023.
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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 Journal Article
In: システム制御情報学会論文誌, vol. 37, no. 1, pp. 12–21, 2023.
@article{futatsugi2023,
title = {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},
author = {{二木 浩司} and {矢入 健久}},
doi = {10.5687/iscie.37.12},
year = {2023},
date = {2023-01-01},
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Masano Natsumeda; Takehisa Yairi
Feature Selection with Partial Autoencoding for Zero-Sample Fault Diagnosis Journal Article
In: IEEE Transactions on Industrial Informatics, vol. 20, no. 2, pp. 2144–2153, 2023.
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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 Proceedings Article
In: Advances in Neural Information Processing Systems 36, pp. 1082–1099, 2023.
@inproceedings{falkiewiczCalibratingNeuralSimulationBased2023,
title = {Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability},
author = {Maciej Falkiewicz and Naoya Takeishi and Imahn Shekhzadeh and Antoine Wehenkel and Arnaud Delaunoy and Gilles Louppe and Alexandros Kalousis},
url = {https://papers.nips.cc/paper_files/paper/2023/hash/03a9a9c1e15850439653bb971a4ad4b3-Abstract-Conference.html},
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booktitle = {Advances in Neural Information Processing Systems 36},
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Naoya Takeishi; Yoshinobu Kawahara
A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores Journal Article
In: Transactions on Machine Learning Research, 2023.
@article{takeishiCharacteristicFunctionShapleyValueBased2023,
title = {A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores},
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year = {2023},
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Samir Khan; Takehisa Yairi; Seiji Tsutsumi; Shinichi Nakasuka
A review of physics-based learning for system health management Journal Article
In: Annual Reviews in Control, vol. 57, pp. 100932, 2023.
@article{khanReviewPhysicsBasedLearning2023,
title = {A review of physics-based learning for system health management},
author = {Samir Khan and Takehisa Yairi and Seiji Tsutsumi and Shinichi Nakasuka},
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Ryota Yagi; Takehisa Yairi; Akira Iwasaki
Navigating the Metaverse: UAV-Based Cross-View Geo-Localization in Virtual Worlds Proceedings Article
In: Proceedings of the 2023 Workshop on UAVs in Multimedia: Capturing the World from a New Perspective, pp. 13–17, 2023.
@inproceedings{yagiNavigatingMetaverseUAVBased2023,
title = {Navigating the Metaverse: UAV-Based Cross-View Geo-Localization in Virtual Worlds},
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Ryosuke Takayama; Masanao Natsumeda; Takehisa Yairi
A semi-supervised RUL prediction with likelihood-based pseudo labeling for suspension histories Proceedings Article
In: Proceedings of the 2023 IEEE International Conference on Prognostics and Health Management, pp. 296–303, 2023.
@inproceedings{takayamaSemiSupervisedRUL2023,
title = {A semi-supervised RUL prediction with likelihood-based pseudo labeling for suspension histories},
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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 Journal Article
In: IEEE Access, vol. 10, pp. 110727–110741, 2022.
@article{nguyenHumanLanguageExplanation2022,
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X. Phong Nguyen; Hung Q. Cao; Khang V. T. Nguyen; Hung Nguyen; Takehisa Yairi
SeCAM: Tightly Accelerate the Image Explanation via Region-Based Segmentation Journal Article
In: IEICE Transactions on Information and Systems, vol. E105.D, no. 8, pp. 1401–1417, 2022.
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Ryosuke Matsuo; Shinya Yasuda; Taichi Kumagai; Natsuhiko Sato; Hiroshi Yoshida; Takehisa Yairi
Residual Reinforcement Learning for Logistics Cart Transportation Journal Article
In: Advanced Robotics, vol. 36, no. 8, pp. 404–421, 2022.
@article{matsuoResidualReinforcementLearning2022,
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Koji Minoda; Takehisa Yairi
3D Human Pose Estimation in Weightless Environments Using a Fisheye Camera Proceedings Article
In: Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4100–4105, 2022.
@inproceedings{minoda3DHumanPose2022,
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Takahiro Hori; Takehisa Yairi
Low-latency LiDAR semantic segmentation Proceedings Article
In: Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 9886–9891, 2022.
@inproceedings{horilowlatencyLiDARSemantic2022,
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Osamu Yoshimatsu; Takehisa Yairi
Impact Analysis of Evaluation Task Setting on a Public Dataset for Rolling Bearing Diagnostics Using Deep Learning Proceedings Article
In: Proceedings of the 2022 61st Annual Conference of the Society of Instrument and Control Engineers, pp. 728–733, 2022.
@inproceedings{yoshimatsuImpactAnalysisEvaluation2022,
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Wenyi Liu; Takehisa Yairi; Nana Tamai
Feature selection for quality prediction under distribution shift Proceedings Article
In: Proceedings of the 2022 61st Annual Conference of the Society of Instrument and Control Engineers, pp. 548–552, 2022.
@inproceedings{liuFeatureSelectionQuality2022,
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Ryosuke Takayama; Takehisa Yairi; Nana Tamai
Nonstationary and Sparse Linear Regression for State Prediction of Artificial Systems Proceedings Article
In: Proceedings of the 2022 61st Annual Conference of the Society of Instrument and Control Engineers, pp. 553–558, 2022.
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Samir Khan; Takehisa Yairi; Shinichi Nakasuka; Seiji Tsutsumi
Reinforcement Learning-based Anomaly Detection for PHM applications Proceedings Article
In: 2022 IEEE Aerospace Conference (AERO), 2022.
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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 Book Section
In: Advances in Condition Monitoring and Structural Health Monitoring, pp. 129–141, 2021.
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title = {A Data-Driven Approach to Anomaly Detection and Health Monitoring for Artificial Satellites},
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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 Journal Article
In: IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 1343–1350, 2021.
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2020
Hidekazu Karino; Takehisa Yairi; Tetsujiro Ninomiya; Koichi Hori
Estimating Aerodynamic Coefficients from Uncertain Data of D-SEND Aircraft with Gaussian Process Regression Journal Article
In: Transactions of the Japan Society for Aeronautical and Space Sciences, vol. 63, no. 6, pp. 257–264, 2020.
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Yoshiyuki Anzai; Takehisa Yairi; Naoya Takeishi; Yuichi Tsuda; Naoko Ogawa
Visual localization for asteroid touchdown operation based on local image features Journal Article
In: Astrodynamics, vol. 4, pp. 149–161, 2020.
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doi = {10.1007/s42064-020-0075-8},
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Takaaki Tagawa; Yukihiro Tadokoro; Takehisa Yairi
Scalable Change Analysis and Representation Using Characteristic Function Journal Article
In: International Journal of Prognostics and Health Management, vol. 11, no. 1, 2020.
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Chun Fui Liew; Takehisa Yairi
Companion unmanned aerial vehicles: A survey Unpublished
2020, (arXiv:2001.04637).
@unpublished{nokey,
title = {Companion unmanned aerial vehicles: A survey},
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Takaaki Tagawa; Yukihiro Tadokoro; Takehisa Yairi
Interactive Anomaly Identification with Erroneous Feedback Journal Article
In: International Journal of Prognostics and Health Management, vol. 11, no. 2, 2020.
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Samir Khan; Takehisa Yairi
Diagnosing Intermittent Faults through Non-linear Analysis Journal Article
In: IFAC-PapersOnLine, vol. 53, no. 2, pp. 10304–10309, 2020.
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2019
Koji Minoda; Takehisa Yairi; Koichi Hori
Data-driven health monitoring of high dimensional time-varying systems by tracking dynamic modes Conference
Asia Pacific Conference of the Prognostics and Health Management Society, Beijing, 2019.
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Danielle M. DeLatte; Sarah T. Crites; Nicholas Guttenberg; Elizabeth J. Tasker; Takehisa Yairi
Segmentation Convolutional Neural Networks for Automatic Crater Detection on Mars Journal Article
In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 9, pp. 2944–2957, 2019.
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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 Journal Article
In: Advances in Space Research, vol. 64, no. 8, pp. 1615–1628, 2019.
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Samir Khan; Chun Fui Liew; Takehisa Yairi; Richard McWilliam
Unsupervised anomaly detection in unmanned aerial vehicles Journal Article
In: Applied Soft Computing, vol. 83, pp. 105650, 2019.
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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 Journal Article
In: 計測と制御, vol. 58, no. 3, pp. 176–181, 2019.
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矢入 健久
典型例で眺める機械学習の様々なタスク Journal Article
In: ガスタービン学会誌, vol. 47, no. 5, pp. 282–287, 2019.
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Riku Sasaki; Naoya Takeishi; Takehisa Yairi; Koichi Hori
Neural Gray-Box Identification of Nonlinear Partial Differential Equations Book Section
In: PRICAI 2019: Trends in Artificial Intelligence, no. 11671, pp. 309–321, 2019.
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Ryo Sakagami; Naoya Takeishi; Takehisa Yairi; Koichi Hori
Visualization Methods for Spacecraft Telemetry Data Using Change-point Detection and Clustering Journal Article
In: Aerospace Technology Japan, vol. 17, no. 2, pp. 244–252, 2019.
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2018
Hidekazu Karino; Takehisa Yairi; Tetsujiro Ninomiya; Koichi Hori
Estimating Aerodynamic Characteristics of D-SEND Aircraft with Gaussian Process Regression Conference
SICE Annual Conference, Nara, 2018.
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Kentaro Abe; Samir Khan; Takehisa Yairi; Chun Fui Liew
Towards Anomaly detection using Variational Long Short-term Memory Autoencoders for System Health Monitoring Control Conference
Joint Workshop on Deep (or Machine) Learning for Safety-Critical Applications in Engineering, Stockholm, 2018.
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Danielle M. DeLatte; Sarah T. Crites; Nicholas Guttenberg; Elizabeth J. Tasker; Takehisa Yairi
Experiments in Segmenting Mars Craters using Convolutional Neural Networks Conference
International Symposium on Artificial Intelligence, Robotics and Automation in Space, Madrid, 2018.
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Danielle M. DeLatte; Sarah T. Crites; Nicholas Guttenberg; Elizabeth J. Tasker; Takehisa Yairi
Exploration of machine learning methods for crater counting on mars Conference
49th Lunar and Planetary Science Conference, The Woodlands, Texas, 2018.
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Samir Khan; Takehisa Yairi
A review on the application of deep learning in system health management Journal Article
In: Mechanical Systems and Signal Processing, vol. 107, pp. 241–265, 2018.
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