| Fusing physics-based and deep learning models for prognostics MA Chao, C Kulkarni, K Goebel, O Fink Reliability Engineering & System Safety 217, 107961, 2022 | 310 | 2022 |
| 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 | 214 | 2021 |
| Real-time model calibration with deep reinforcement learning Y Tian*, M Arias Chao*, C Kulkarni, K Goebel, O Fink Mechanical Systems and Signal Processing 165, 108284, 2022 | 57 | 2022 |
| 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, 2019 | 53* | 2019 |
| Uncertainty-Aware Prognosis via Deep Gaussian Process L Biggio, A Wieland, MA Chao, I Kastanis, O Fink IEEE Access 9, 123517-123527, 2021 | 50* | 2021 |
| Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders MA Chao, BT Adey, O Fink Neurocomputing 454, 324-338, 2021 | 38 | 2021 |
| Stochastic axial compressor variable geometry schedule optimisation L Gallar, M Arias, V Pachidis, R Singh Aerospace Science and Technology 15 (5), 366-374, 2011 | 38 | 2011 |
| Method for operating a gas turbine plant and gas turbine plant for implementing the method MA Chao, B Wippel, C Balmer, R Jakoby US Patent 9,752,504, 2017 | 34 | 2017 |
| Compressor variable geometry schedule optimisation using genetic algorithms L Gallar, M Arias, V Pachidis, P Pilidis Turbo Expo: Power for Land, Sea, and Air 48852, 425-434, 2009 | 25 | 2009 |
| Learning to Calibrate Battery Models in Real-Time with Deep Reinforcement Learning A Unagar, Y Tian, MA Chao, O Fink Energies 14 (5), 1361, 2021 | 24 | 2021 |
| Calibration and uncertainty quantification of gas turbine performance models MA Chao, DS Lilley, P Mathé, V Schloßhauer Turbo Expo: Power for Land, Sea, and Air 56765, V07AT29A001, 2015 | 13 | 2015 |
| Method for operating a power plant MA Chao, W Reiter, DS Lilley US Patent App. 15/241,269, 2017 | 9 | 2017 |
| PHM Society Data Challenge 2021 MA Chao, C Kulkarni, K Goebel, O Fink PHM Society, 1-6, 2021 | 7 | 2021 |
| Physics-Informed Machine Learning for Predictive Maintenance: Applied Use-Cases LG Huber, T Palmé, MA Chao 2023 10th IEEE Swiss Conference on Data Science (SDS), 66-72, 2023 | 5 | 2023 |
| Feature selecting hierarchical neural network for industrial system health monitoring: catching informative features with LASSO G Michau, M Arias Chao, O Fink Proceedings of the Annual Conference of the PHM Society 10 (1), 494, 2018 | 5 | 2018 |
| Combining Deep Learning and Physics-Based Performance Models for Diagnostics and Prognostics M Arias Chao ETH Zurich, 2021 | 4 | 2021 |
| Method for determining at least one firing temperature for controlling a gas turbine and gas turbine for performing the method MA Chao, A Nemet, UR Steiger, DS Lilley US Patent App. 14/491,172, 2015 | 4 | 2015 |
| A Novel Intake Concept for Flue Gas Recirculation to Enhance CCS in an Industrial Gas Turbine RC Payne, M Arias Chao, V Stefanis ASME Turbo Expo 2014: Turbine Technical Conference and Exposition, 2014 | 4 | 2014 |
| A benchmark on uncertainty quantification for deep learning prognostics L Basora, A Viens, MA Chao, X Olive Reliability Engineering & System Safety, 110513, 2024 | 3 | 2024 |
| Unsupervised Physics-Informed Health Indicator Discovery for Complex Systems K Bajarunas, M Baptista, K Goebel, MA Chao Proceedings of the Annual Conference of the Prognostics and Health …, 2023 | 2* | 2023 |
Olga FinkLaboratory of Intelligent Maintenance and Operations Systems, EPFLVerified email at epfl.ch
