| 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 | 183 | 2019 |
| Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer G Michau, O Fink Knowledge-Based Systems 216, 106816, 2021 | 155 | 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 | 122 | 2022 |
| Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series G Michau, O Fink arXiv preprint arXiv:2105.00899, 2021 | 115 | 2021 |
| 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 | 80 | 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 | 76 | 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 | 71 | 2017 |
| 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 | 54 | 2023 |
| 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 | 45 | 2019 |
| 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 | 44 | 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 | 44 | 2016 |
| 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 | 41* | 2021 |
| Unsupervised Fault Detection in Varying Operating Conditions G Michau, O Fink arXiv preprint arXiv:1907.06481, 2019 | 39 | 2019 |
| Interpretable Detection of Partial Discharge in Power Lines with Deep Learning G Michau, CC Hsu, O Fink Sensors 21 (6), 2154, 2021 | 36 | 2021 |
| 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 | 36 | 2018 |
| 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 | 35 | 2017 |
| 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 | 19 | 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 | 17 | 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 | 15 | 2015 |
| Canonical polyadic decomposition and deep learning for machine fault detection G Frusque, M Gabriel, F Olga PHM Society European Conference 6 (1), 9-9, 2021 | 14 | 2021 |
Olga FinkLaboratory of Intelligent Maintenance and Operations Systems, EPFLVerified email at epfl.ch
