output
20122026
most citedContemporary Symbolic Regression Methods and their Relative Performance

144 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing 2025Show all

11 papers · 1 filter

cs.LG2025★ 3 cited

Introduction to Symbolic Regression in the Physical Sciences

Deaglan J. Bartlett, Harry Desmond, Pedro G. Ferreira +1

Symbolic regression (SR) has emerged as a powerful method for uncovering interpretable mathematical relationships from data, offering a novel route to both scientific discovery and…

cs.LG2025★ 2 cited

Can Synthetic Data Improve Symbolic Regression Extrapolation Performance?

Fitria Wulandari Ramlan, Colm O'Riordan, Gabriel Kronberger +1

Many machine learning models perform well when making predictions within the training data range, but often struggle when required to extrapolate beyond it. Symbolic regression (SR…

cs.CV2025

Detection and Measurement of Hailstones with Multimodal Large Language Models

Moritz Alker, David C. Schedl, Andreas Stöckl

This study examines the use of social media and news images to detect and measure hailstones, utilizing pre-trained multimodal large language models. The dataset for this study com…

math.CV2025★ 8 cited

Weighted Chebyshev Polynomials on Compact Subsets of the Complex Plane

Galen Novello, Klaus Schiefermayr, Maxim Zinchenko

We study weighted Chebyshev polynomials on compact subsets of the complex plane with respect to a bounded weight function. We establish existence and uniqueness of weighted Chebysh…

cs.PL2025★ 1 cited

Generating Inputs for Grammar Mining using Dynamic Symbolic Execution

Andreas Pointner, Josef Pichler, Herbert Prähofer

A vast number of software systems include components that parse and process structured input. In addition to programming languages, which are analyzed by compilers or interpreters,…

astro-ph.CO2025★ 4 cited

syren-baryon: Analytic emulators for the impact of baryons on the matter power spectrum

Lukas Kammerer, Deaglan J. Bartlett, Gabriel Kronberger +2

Baryonic physics has a considerable impact on the distribution of matter in our Universe on scales probed by current and future cosmological surveys, acting as a key systematic in…

eess.SY2025★ 1 cited

Optimizing Energy Consumption in Stochastic Production Systems: Using a Simulation-Based Approach for Stopping Policy

Balwin Bokor, Klaus Altendorfer, Andrea Matta

In response to the escalating need for sustainable manufacturing, this study introduces a Simulation-Based Approach (SBA) to model a stopping policy for energy-intensive stochastic…

cs.LG2025★ 5 cited

Call for Action: towards the next generation of symbolic regression benchmark

Guilherme S. Imai Aldeia, Hengzhe Zhang, Geoffrey Bomarito +5

Symbolic Regression (SR) is a powerful technique for discovering interpretable mathematical expressions. However, benchmarking SR methods remains challenging due to the diversity o…

eess.SY2025★ 2 cited

Release Date Optimization in MRP Using Clearing Functions

Wolfgang Seiringer, Klaus Altendorfer, Reha Uzsoy

This paper integrates a clearing function (CF)-based release planning approach into Material Requirements Planning (MRP) to address its limitations in modeling capacity constraints…

cs.LG2025★ 3 cited

rEGGression: an Interactive and Agnostic Tool for the Exploration of Symbolic Regression Models

Fabricio Olivetti de Franca, Gabriel Kronberger

Regression analysis is used for prediction and to understand the effect of independent variables on dependent variables. Symbolic regression (SR) automates the search for non-linea…

cs.LG2025★ 6 cited

Improving Genetic Programming for Symbolic Regression with Equality Graphs

Fabricio Olivetti de Franca, Gabriel Kronberger

The search for symbolic regression models with genetic programming (GP) has a tendency of revisiting expressions in their original or equivalent forms. Repeatedly evaluating equiva…