2 papers
cs.LG2026
Universal hidden monotonic trend estimation with contrastive learning
Edouard Pineau, Sébastien Razakarivony
In this paper, we describe a universal method for extracting the underlying monotonic trend factor from time series data. We propose an approach related to the Mann-Kendall test, a…
cs.LG2026
A Machine Learning Framework for Turbofan Health Estimation via Inverse Problem Formulation
Milad Leyli-Abadi, Lucas Thil, Sebastien Razakarivony +2
Estimating the health state of turbofan engines is a challenging ill-posed inverse problem, hindered by sparse sensing and complex nonlinear thermodynamics. Research in this area r…