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20152026
most citedInterpretability in Symbolic Regression: a benchmark of Explanatory Methods using the Feynman data set

22 citations · 50 across the 10 of their papers we have counts for

collaborators

13 papers

cs.LG2026

Are you sure? A Comprehensive and Comprehensible Survey of Uncertainty Quantification in Symbolic Regression

Julia Reuter, Fabricio Olivetti de Franca

Symbolic regression (SR) is a class of methods that systematically explore the space of mathematical functions to discover models that accurately capture the underlying relationshi…

cs.NE2026

Guiding Multi-Objective Genetic Programming with Description Length Improves Symbolic Regression Solutions

Gabriel Kronberger, Fabricio Olivetti de Franca, Deaglan J. Bartlett +2

Symbolic regression with genetic programming (GPSR) may suffer from overfitting and structural bloat, especially when noise is present. In this paper we evaluate description length…

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…

cs.PL2024

Going Bananas! - Unfolding Program Synthesis with Origami

Matheus Campos Fernandes, Fabrício Olivetti de França, Emilio Francesquini

Automatically creating a computer program using input-output examples can be a challenging task, especially when trying to synthesize computer programs that require loops or recurs…

cs.LG2024★ 22 cited

Interpretability in Symbolic Regression: a benchmark of Explanatory Methods using the Feynman data set

Guilherme Seidyo Imai Aldeia, Fabricio Olivetti de Franca

In some situations, the interpretability of the machine learning models plays a role as important as the model accuracy. Interpretability comes from the need to trust the predictio…