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20142025
most citedInterpretability in Symbolic Regression: a benchmark of Explanatory Methods using the Feynman data set

22 citations · 47 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG20255 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…

cs.NE20253 cited

TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming

Roman Kalkreuth, Fabricio Olivetti de França, Julian Dierkes +4

Over the years, genetic programming (GP) has evolved, with many proposed variations, especially in how they represent a solution. Being essentially a program synthesis algorithm, i…

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.NE20241 cited

Minimum variance threshold for epsilon-lexicase selection

Guilherme Seidyo Imai Aldeia, Fabricio Olivetti de Franca, William G. La Cava

Parent selection plays an important role in evolutionary algorithms, and many strategies exist to select the parent pool before breeding the next generation. Methods often rely on…

cs.LG202422 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…

cs.NE20245 cited

Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing

Guilherme Seidyo Imai Aldeia, Fabricio Olivetti de Franca, William G. La Cava

Symbolic regression (SR) searches for parametric models that accurately fit a dataset, prioritizing simplicity and interpretability. Despite this secondary objective, studies point…