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Olga Fink
Olga Fink
Laboratory of Intelligent Maintenance and Operations Systems, EPFL
Verified email at epfl.ch
Title
Cited by
Cited by
Year
Potential, challenges and future directions for deep learning in prognostics and health management applications
O Fink, Q Wang, M Svensén, P Dersin, WJ Lee, M Ducoffe
Engineering Applications of Artificial Intelligence 92, 103678, 2020
2682020
Combined fault location and classification for power transmission lines fault diagnosis with integrated feature extraction
YQ Chen, O Fink, G Sansavini
IEEE Transactions on Industrial Electronics 65 (1), 561-569, 2018
1912018
Two machine learning approaches for short-term wind speed time-series prediction
R Ak, O Fink, E Zio
IEEE transactions on neural networks and learning systems 27 (8), 1734-1747, 2016
1672016
Fusing physics-based and deep learning models for prognostics
MA Chao, C Kulkarni, K Goebel, O Fink
Reliability Engineering & System Safety 217, 107961, 2022
1232022
Predicting component reliability and level of degradation with complex-valued neural networks
O Fink, E Zio, U Weidmann
Reliability Engineering & System Safety 121, 198-206, 2014
1232014
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
1132019
Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics
M Arias Chao, C Kulkarni, K Goebel, O Fink
Data 6 (1), 5, 2021
842021
Continual test-time domain adaptation
Q Wang, O Fink, L Van Gool, D Dai
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
772022
Domain adaptive semantic segmentation with self-supervised depth estimation
Q Wang, D Dai, L Hoyer, L Van Gool, O Fink
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
702021
Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer
G Michau, O Fink
Knowledge-Based Systems 216, 106816, 2021
482021
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
482019
Missing-class-robust domain adaptation by unilateral alignment
Q Wang, G Michau, O Fink
IEEE Transactions on Industrial Electronics 68 (1), 663-671, 2020
422020
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
40*2022
Off-policy reinforcement learning for efficient and effective gan architecture search
Y Tian, Q Wang, Z Huang, W Li, D Dai, M Yang, J Wang, O Fink
European Conference on Computer Vision, 175-192, 2020
402020
Fault detection based on signal reconstruction with Auto-Associative Extreme Learning Machines
Y Hu, T Palmé, O Fink
Engineering Applications of Artificial Intelligence 57, 105-117, 2017
372017
Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models
M Arias Chao, C Kulkarni, K Goebel, O Fink
International Journal of Prognostics and Health Management 10 (033), 2019
31*2019
Novelty detection by multivariate kernel density estimation and growing neural gas algorithm
O Fink, E Zio, U Weidmann
Mechanical Systems and Signal Processing 50, 427-436, 2015
302015
Deep feature learning network for fault detection and isolation
G Michau, T Palm, O Fink
Annual Conference of the PHM Society 9 (1), 2017
292017
Fuzzy Classification With Restricted Boltzman Machines and Echo-State Networks for Predicting Potential Railway Door System Failures
O Fink, E Zio, U Weidmann
IEEE Transactions on Reliability 64 (3), 861-868, 2015
292015
Assessment of maintenance strategies for railway vehicles using Petri-nets
D Eisenberger, O Fink
Transportation Research Procedia 27, 205-214, 2017
272017
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