26 citations · 38 across the 2 of their papers we have counts for
3 papers
Real-Time Model Calibration with Deep Reinforcement Learning
Yuan Tian, Manuel Arias Chao, Chetan Kulkarni +2
The dynamic, real-time, and accurate inference of model parameters from empirical data is of great importance in many scientific and engineering disciplines that use computational…
Fusing Physics-based and Deep Learning Models for Prognostics
Manuel Arias Chao, Chetan Kulkarni, Kai Goebel +1
Physics-based and data-driven models for remaining useful lifetime (RUL) prediction typically suffer from two major challenges that limit their applicability to complex real-world…
Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models
Manuel Arias Chao, Chetan Kulkarni, Kai Goebel +1
With the increased availability of condition monitoring data and the increased complexity of explicit system physics-based models, the application of data-driven approaches for fau…