Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse Optimization used to identify physical process, numerical schemes, and LES subgrid ...

Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse Optimization used to identify physical process, numerical schemes, and LES subgrid ...

Unlike traditional regression, which fits data to predefined models, symbolic regression searches for the underlying mathematical structures from scratch. This approach has gained prominence in ...

Artificial Intelligence and Deep learning have brought about some great advancements in the field of technology. They are enabling robots to perform activities that were previously thought to be ...

Coupled with symbolic regression (SR), which aims to uncover interpretable mathematical expressions directly from data, these techniques synergistically offer robust frameworks for model discovery.

Symbolic regression is aimed at discovering mathematical expressions, in symbolic form, that fit a given sample of data points. While genetic programming (GP) constitutes a powerful tool for solving ...