2023
Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
NeurIPS 2023spotlight
When deploying machine learning estimators in science and engineering (SAE) domains, it is critical to avoid failed estimations that can have disastrous consequences, e.g., in aero engine design. This work focuses on detecting and correcting failed state estimations before adopting them in SAE i…