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cs.LG2023★ 1 cited
Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
Ruiyuan Kang, Tingting Mu, Panos Liatsis +1
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…
cs.NE2023
EEE, Remediating the failure of machine learning models via a network-based optimization patch
Ruiyuan Kang, Dimitrios Kyritsis, Panos Liatsis
A network-based optimization approach, EEE, is proposed for the purpose of providing validation-viable state estimations to remediate the failure of pretrained models. To improve o…