activity
20232026
most citedIntroducing Thermodynamics-Informed Symbolic Regression -- A Tool for Thermodynamic Equations of State Development

7 citations · 7 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2026

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…

cs.LG2024

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…

cs.LG2024

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…

cs.LG2023★ 7 cited

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…

math.NA2023

Uncertainty Propagation of Initial Conditions in Thermal Models

Alexandra Bünger, Roland Herzog, Andreas Naumann +1

The operation of machine tools often demands a highly accurate knowledge of the tool center point's (TCP) position. The displacement of the TCP over time can be inferred from therm…