Gabriel Michau
Orcid: 0000-0001-6882-2906
According to our database1,
Gabriel Michau
authored at least 23 papers
between 2015 and 2023.
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Bibliography
2023
Controlled generation of unseen faults for <i>Partial</i> and <i>Open-Partial</i> domain adaptation.
Reliab. Eng. Syst. Saf., 2023
2022
Contrastive Feature Learning for Fault Detection and Diagnostics in Railway Applications.
CoRR, 2022
Controlled Generation of Unseen Faults for Partial and OpenSet&Partial Domain Adaptation.
CoRR, 2022
2021
IEEE Trans. Ind. Electron., 2021
Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types.
Sensors, 2021
Sensors, 2021
Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer.
Knowl. Based Syst., 2021
CoRR, 2021
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series.
CoRR, 2021
Decision Support System for an Intelligent Operator of Utility Tunnel Boring Machines.
CoRR, 2021
2020
Interpretable Partial Discharge Detection with Temporal Convolution and Pulse Activation Maps: An application to Power Lines.
CoRR, 2020
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks.
CoRR, 2020
Time Series to Images: Monitoring the Condition of Industrial Assets with Deep Learning Image Processing Algorithms.
CoRR, 2020
CoRR, 2020
Improving generalization of deep fault detection models in the presence of mislabeled data.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020
2019
Fully Unsupervised Feature Alignment for Critical System Health Monitoring with Varied Operating Conditions.
CoRR, 2019
Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019
2018
Feature Learning for Fault Detection in High-Dimensional Condition-Monitoring Signals.
CoRR, 2018
2017
IEEE Trans. Signal Inf. Process. over Networks, 2017
IEEE Trans. Intell. Transp. Syst., 2017
2015
Estimating link-dependent Origin-Destination matrices from sample trajectories and traffic counts.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015