Publication

下記の他に、まとめきれていない国内学会等での発表が多数あります。

78 entries « 1 of 2 »

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.

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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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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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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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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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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.

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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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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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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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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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).

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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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78 entries « 1 of 2 »