5 papers · 1 filter
Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing
Viktor Martinek, Roland Herzog
Symbolic regression aims to find symbolic expressions that describe datasets. Due to its inherent interpretability, symbolic regression (SR) is a powerful paradigm for scientific d…
Fast Symbolic Regression Benchmarking
Viktor Martinek
Symbolic regression (SR) uncovers mathematical models from data. Several benchmarks have been proposed to compare the performance of SR algorithms. However, existing ground-truth r…
Unit-Aware Genetic Programming for the Development of Empirical Equations
Julia Reuter, Viktor Martinek, Roland Herzog +1
When developing empirical equations, domain experts require these to be accurate and adhere to physical laws. Often, constants with unknown units need to be discovered alongside th…
Shape Constraints in Symbolic Regression using Penalized Least Squares
Viktor Martinek, Julia Reuter, Ophelia Frotscher +3
We study the addition of shape constraints (SC) and their consideration during the parameter identification step of symbolic regression (SR). SC serve as a means to introduce prior…
Introducing Thermodynamics-Informed Symbolic Regression -- A Tool for Thermodynamic Equations of State Development
Viktor Martinek, Ophelia Frotscher, Markus Richter +1
Thermodynamic equations of state (EOS) are essential for many industries as well as in academia. Even leaving aside the expensive and extensive measurement campaigns required for t…