3 citations · 7 across the 4 of their papers we have counts for
3 papers · 1 filter
Scaling Up Unbiased Search-based Symbolic Regression
Paul Kahlmeyer, Joachim Giesen, Michael Habeck +1
In a regression task, a function is learned from labeled data to predict the labels at new data points. The goal is to achieve small prediction errors. In symbolic regression, the…
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,…
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…