9 citations · 14 across the 4 of their papers we have counts for
4 papers
Sound Interval-Based Synthesis for Probabilistic Programs
Guilherme Espada, Alcides Fonseca
Probabilistic programming has become a standard practice to model stochastic events and learn about the behavior of nature in different scientific contexts, ranging from Genetics a…
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…
Semantically Rich Local Dataset Generation for Explainable AI in Genomics
Pedro Barbosa, Rosina Savisaar, Alcides Fonseca
Black box deep learning models trained on genomic sequences excel at predicting the outcomes of different gene regulatory mechanisms. Therefore, interpreting these models may provi…
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition
F. O. de Franca, M. Virgolin, M. Kommenda +21
Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main attraction of this approach is that it returns an interpretable model tha…