2 papers
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…
cs.LG2025
Study Design and Demystification of Physics Informed Neural Networks for Power Flow Simulation
Milad Leyli-abadi, Antoine Marot, Jérôme Picault
In the context of the energy transition, with increasing integration of renewable sources and cross-border electricity exchanges, power grids are encountering greater uncertainty a…