Gabriel Michau
Gabriel Michau
Project Manager CBM, Stadler Service AG
Verified email at
Cited by
Cited by
Domain adaptive transfer learning for fault diagnosis
Q Wang, G Michau, O Fink
2019 Prognostics and System Health Management Conference (PHM-Paris), 279-285, 2019
Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer
G Michau, O Fink
Knowledge-Based Systems 216, 106816, 2021
Temporal signals to images: Monitoring the condition of industrial assets with deep learning image processing algorithms
GR Garcia, G Michau, M Ducoffe, JS Gupta, O Fink
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2022
Feature learning for fault detection in high-dimensional condition-monitoring signals
G Michau, Y Hu, T Palmé, O Fink
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2019
Missing-class-robust domain adaptation by unilateral alignment
Q Wang, G Michau, O Fink
IEEE Transactions on Industrial Electronics 68 (1), 663-671, 2020
Bluetooth Data in an Urban Context: Retrieving Vehicle Trajectories
G Michau, A Nantes, A Bhaskar, E Chung, P Abry, P Borgnat
IEEE Transactions on Intelligent Transportation Systems 18 (9), 2377-2386, 2017
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series
G Michau, O Fink
arXiv preprint arXiv:2105.00899, 2021
A primal-dual algorithm for link dependent origin destination matrix estimation
G Michau, N Pustelnik, P Borgnat, P Abry, A Nantes, A Bhaskar, E Chung
IEEE Transactions on Signal and Information Processing over Networks 3 (1 …, 2016
Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types
K Rombach, G Michau, O Fink
Sensors 21 (10), 3550, 2021
Domain Adaptation for One-Class Classification: Monitoring the Health of Critical Systems Under Limited Information
G Michau, O Fink
International Journal of Prognostics and Health Management 10 (028), 11, 2019
Deep Feature Learning Network for Fault Detection and Isolation
G Michau, T Palmé, O Fink
Annual Conference of the Prognostics and Health Management Society 2017 …, 2017
Fleet PHM for Critical Systems: Bi-level Deep Learning Approach for Fault Detection
G Michau, T Palmé, O Fink
PHM Society European Conference 4 (1), 2018
Unsupervised Fault Detection in Varying Operating Conditions
G Michau, O Fink
arXiv preprint arXiv:1907.06481, 2019
Decision Support System for an Intelligent Operator of Utility Tunnel Boring Machines
G Rodriguez Garcia, G Michau, HH Einstein, O Fink
arXiv e-prints, arXiv: 2101.02463, 2021
Interpretable Detection of Partial Discharge in Power Lines with Deep Learning
G Michau, CC Hsu, O Fink
Sensors 21 (6), 2154, 2021
Controlled generation of unseen faults for Partial and Open-Partial domain adaptation
K Rombach, G Michau, O Fink
Reliability Engineering & System Safety 230, 108857, 2023
Retrieving dynamic origin-destination matrices from Bluetooth data
G Michau, A Nantes, E Chung, P Abry, P Borgnat
Transportation Research Board (TRB) 93rd Annual Meeting Compendium of Papers …, 2014
Combining traffic counts and Bluetooth data for link-origin-destination matrix estimation in large urban networks: The Brisbane case study
G Michau, N Pustelnik, P Borgnat, P Abry, A Bhaskar, E Chung
arxiv, 2017
Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts
G Michau, P Borgnat, N Pustelnik, P Abry, A Nantes, E Chung
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
Towards the retrieval of accurate OD matrices from Bluetooth data: lessons learned from 2 years of data
G Michau, A Nantes, E Chung
Australasian Transport Research Forum 2013 Proceedings, 1-11, 2013
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