Manuel Arias Chao

According to our database, Manuel Arias Chao authored at least 12 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

A Benchmark on Uncertainty Quantification for Deep Learning Prognostics.

Luis Basora, Arthur Viens, Manuel Arias Chao, Xavier Olive

CoRR, 2023

Physics-Informed Machine Learning for Predictive Maintenance: Applied Use-Cases.

Lilach Goren Huber, Thomas Palmé, Manuel Arias Chao

Proceedings of the 10th IEEE Swiss Conference on Data Science, 2023

2022

Fusing physics-based and deep learning models for prognostics.

Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

Reliab. Eng. Syst. Saf., 2022

2021

Combining Deep Learning and Physics-Based Performance Models for Diagnostics and Prognostics.

Manuel Arias Chao

PhD thesis, 2021

Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders.

Manuel Arias Chao, Bryan T. Adey, Olga Fink

Neurocomputing, 2021

Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics.

Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

Data, 2021

Uncertainty-aware Remaining Useful Life predictor.

Luca Biggio, Alexander Wieland, Manuel Arias Chao, Iason Kastanis, Olga Fink

CoRR, 2021

Uncertainty-Aware Prognosis via Deep Gaussian Process.

Luca Biggio, Alexander Wieland, Manuel Arias Chao, Iason Kastanis, Olga Fink

IEEE Access, 2021

2020

Battery Model Calibration with Deep Reinforcement Learning.

Ajaykumar Unagar, Yuan Tian, Manuel Arias Chao, Olga Fink

CoRR, 2020

Real-Time Model Calibration with Deep Reinforcement Learning.

Yuan Tian, Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

CoRR, 2020

2019

Knowledge-Induced Learning with Adaptive Sampling Variational Autoencoders for Open Set Fault Diagnostics.

Manuel Arias Chao, Bryan T. Adey, Olga Fink

CoRR, 2019

Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models.

Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink

CoRR, 2019