3 papers
cs.LG2025
A Surrogate-Augmented Symbolic CFD-Driven Training Framework for Accelerating Multi-objective Physical Model Development
Yuan Fang, Fabian Waschkowski, Maximilian Reissmann +3
Computational Fluid Dynamics (CFD)-driven training combines machine learning (ML) with CFD solvers to develop physically consistent closure models with improved predictive accuracy…
cs.NE2025
Accelerating evolutionary exploration through language model-based transfer learning
Maximilian Reissmann, Yuan Fang, Andrew S. H. Ooi +1
Gene expression programming is an evolutionary optimization algorithm with the potential to generate interpretable and easily implementable equations for regression problems. Despi…
math.OC2024
Constraining Genetic Symbolic Regression via Semantic Backpropagation
Maximilian Reissmann, Yuan Fang, Andrew Ooi +1
Evolutionary symbolic regression approaches are powerful tools that can approximate an explicit mapping between input features and observation for various problems. However, ensuri…