2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Analyzing Generalization in Pre-Trained Symbolic Regression
Henrik Voigt, Paul Kahlmeyer, Kai Lawonn +2
Symbolic regression algorithms search a space of mathematical expressions for formulas that explain given data. Transformer-based models have emerged as a promising, scalable appro…
cs.LG2025★ 2 cited
Discovering Symmetries of ODEs by Symbolic Regression
Paul Kahlmeyer, Niklas Merk, Joachim Giesen
Solving systems of ordinary differential equations (ODEs) is essential when it comes to understanding the behavior of dynamical systems. Yet, automated solving remains challenging,…
cs.LG2025★ 2 cited
Dimension Reduction for Symbolic Regression
Paul Kahlmeyer, Markus Fischer, Joachim Giesen
Solutions of symbolic regression problems are expressions that are composed of input variables and operators from a finite set of function symbols. One measure for evaluating symbo…