Notice détaillée
Titre
IMOS
Formal Name (French)
Systèmes intelligents de maintenance et d'opérations
Formal Name (English)
Intelligent Maintenance and Operations Systems
Lab Manager
Fink, Olga
Group ID
U14193
Auteurs affilié
Faghih Niresi, Keivan
Fink, Olga
Forest, Florent Evariste
Frusque, Gaëtan Michel
Gabriel, Christine
Garmaev, Sergei
Nejjar, Ismail
Sharma, Vinay
Sun, Han
Theiler, Raffael Pascal
Viscione, Michele
Wei, Amaury
Xu, Chenghao
Zhang, Zepeng
Zhao, Mengjie
Fink, Olga
Forest, Florent Evariste
Frusque, Gaëtan Michel
Gabriel, Christine
Garmaev, Sergei
Nejjar, Ismail
Sharma, Vinay
Sun, Han
Theiler, Raffael Pascal
Viscione, Michele
Wei, Amaury
Xu, Chenghao
Zhang, Zepeng
Zhao, Mengjie
Institut
IIC
Faculté
ENAC
Note
Members of IMOS-unit
Lien extérieur
https://iic.epfl.ch/
Publications
A Comparison of Residual-based Methods on Fault Detection
Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions
DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices
Graph neural networks for dynamic modeling of roller bearings
Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity mar[...]
Predictive health assessment for lithium-ion batteries with probabilistic degradation prediction and accelerating aging detection
Real-time model calibration with deep reinforcement learning
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units
SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
Spatial-Temporal Graph Attention Fuser for Calibration in IoT Air Pollution Monitoring Systems
Voir toutes les publications (50)
Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions
DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices
Graph neural networks for dynamic modeling of roller bearings
Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity mar[...]
Predictive health assessment for lithium-ion batteries with probabilistic degradation prediction and accelerating aging detection
Real-time model calibration with deep reinforcement learning
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units
SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
Spatial-Temporal Graph Attention Fuser for Calibration in IoT Air Pollution Monitoring Systems
Voir toutes les publications (50)
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