3 papers
cs.CE2026
Physics-Informed Neural Networks and Sequence Encoder: Application to heating and early cooling of thermo-stamping process
Mouad Elaarabi, Domenico Borzacchiello, Philippe Le Bot +2
In a previous work (Elaarabi et al., 2025b), the Sequence Encoder for online dynamical system identification (Elaarabi et al., 2025a) and its combination with PINN (PINN-SE) were i…
cs.LG2025
Hybrid Adaptive Modeling in Process Monitoring: Leveraging Sequence Encoders and Physics-Informed Neural Networks
Mouad Elaarabi, Domenico Borzacchiello, Philippe Le Bot +2
In this work, we explore the integration of Sequence Encoding for Online Parameter Identification with Physics-Informed Neural Networks to create a model that, once trained, can be…
cs.LG2025
Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks
Mouad Elaarabi, Domenico Borzacchiello, Yves Le Guennec +2
The promising outcomes of dynamical system identification techniques, such as SINDy [Brunton et al. 2016], highlight their advantages in providing qualitative interpretability and…