Mathematical models used for the representation of (bio)-chemical processes can be
grouped into two broad paradigms: white-box or mechanistic models, completely based on …

In recent years, symbolic regression has been of wide interest to provide an interpretable
symbolic representation of potentially large data relationships. Initially circled to genetic …

This research paper introduces a new form of Implied Volatility calculation with Symbolic
Regression suited for high-frequency trading. The solutions are easily migratable to …

Symbolic regression represents a critical challenge in computer science, aiming to derive
accurate equations for given datasets. The classical symbolic regression algorithm, Neuro …

Black-box optimization (BBO) algorithms are concerned with finding the best solutions for
problems with missing analytical details. Most classical methods for such problems are …

Je me dois de remercier toutes les personnes grâce à qui ces années se sont passées dans
les meilleures conditions possibles et ont contribué de près ou de loin à la réussite de cette …

In the construction industry, cement is widely used, and its quality standards are particularly
stringent. Among these standards, the compressive strength of cement is one of the most …

Neuro-Encoded Expression Programming (NEEP) implements the continuous coding for the
discrete solution through recurrent neural networks (RNNs), and smooths sharpness of the …

The ever-growing accumulation of data makes automated distillation of understandable
models from that data ever-more desirable. Deriving equations directly from data using …