58 citations · 112 across the 17 of their papers we have counts for
17 papers
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…
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…
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…
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…
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…
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…
The Inefficiency of Genetic Programming for Symbolic Regression
Gabriel Kronberger, Fabricio Olivetti de Franca, Harry Desmond +2
We analyse the search behaviour of genetic programming for symbolic regression in practically relevant but limited settings, allowing exhaustive enumeration of all solutions. This…
Origami: (un)folding the abstraction of recursion schemes for program synthesis
Matheus Campos Fernandes, Fabricio Olivetti de Franca, Emilio Francesquini
Program synthesis with Genetic Programming searches for a correct program that satisfies the input specification, which is usually provided as input-output examples. One particular…
Multi-View Symbolic Regression
Etienne Russeil, Fabrício Olivetti de França, Konstantin Malanchev +6
Symbolic regression (SR) searches for analytical expressions representing the relationship between a set of explanatory and response variables. Current SR methods assume a single d…
HOTGP -- Higher-Order Typed Genetic Programming
Matheus Campos Fernandes, Fabrício Olivetti de França, Emilio Francesquini
Program synthesis is the process of generating a computer program following a set of specifications, which can be a high-level description of the problem and/or a set of input-outp…
A Greedy Search Tree Heuristic for Symbolic Regression
Fabricio Olivetti de Franca
Symbolic Regression tries to find a mathematical expression that describes the relationship of a set of explanatory variables to a measured variable. The main objective is to find…
An electronic-game framework for evaluating coevolutionary algorithms
Karine da Silva Miras de Araújo, Fabrício Olivetti de França
One of the common artificial intelligence applications in electronic games consists of making an artificial agent learn how to execute some determined task successfully in a game e…
The message does not matter: the influence of the network on information diffusion
Fabricio Olivetti de Franca, Denise Hideko Goya, Claudio Luis de Camargo Penteado
How an information spreads throughout a social network is a valuable knowledge sought by many groups such as marketing enterprises and political parties. If they can somehow predic…
A Hash-based Co-Clustering Algorithm for Categorical Data
Fabricio Olivetti de França
Many real-life data are described by categorical attributes without a pre-classification. A common data mining method used to extract information from this type of data is clusteri…
A Flexible Fitness Function for Community Detection in Complex Networks
Fabricio Olivetti de Franca, Guilherme Palermo Coelho
Most community detection algorithms from the literature work as optimization tools that minimize a given \textit{fitness function}, while assuming that each node belongs to a singl…
Maximizing Diversity for Multimodal Optimization
Fabricio Olivetti de Franca
Most multimodal optimization algorithms use the so called \textit{niching methods}~\cite{mahfoud1995niching} in order to promote diversity during optimization, while others, like \…
Iterative Universal Hash Function Generator for Minhashing
Fabricio Olivetti de Franca
Minhashing is a technique used to estimate the Jaccard Index between two sets by exploiting the probability of collision in a random permutation. In order to speed up the computati…