Symbolic Regression by Grammar-based Multi-Gene Genetic Programming. - Jan Zegklitz; Petr Posík (GECCO (Companion), 2015)

Model Selection and Overfitting in Genetic Programming: Empirical Study. - Jan Zegklitz; Petr Posík (GECCO (Companion), 2015)

Innovative default prediction approach. - Július Bems; Oldrich Starý; Martin Macas; Jan Zegklitz; Petr Posík (Expert Syst. Appl., 2015)

Hybrid Single Node Genetic Programming for Symbolic Regression. - Jirí Kubalík; Eduard Alibekov; Jan Zegklitz; Robert Babuska (Trans. Comput. Collect. Intell., 2016)

Linear combinations of features as leaf nodes in symbolic regression. - Jan Zegklitz; Petr Posík (GECCO (Companion), 2017)

Symbolic Regression Algorithms with Built-in Linear Regression. - Jan Zegklitz; Petr Posík (CoRR, 2017)

Learning Linear Feature Space Transformations in Symbolic Regression. - Jan Zegklitz; Petr Posík (CoRR, 2017)

Sequential Model Building in Symbolic Regression. - Jan Zegklitz; Petr Posík (ITAT, 2019)

Symbolic regression in dynamic scenarios with gradually changing targets. - Jan Zegklitz; Petr Posík (Appl. Soft Comput., 2019)

Symbolic Regression Methods for Reinforcement Learning. - Jirí Kubalík; Erik Derner; Jan Zegklitz; Robert Babuska (IEEE Access, 2021)

Control of Magnetic Manipulator Using Reinforcement Learning Based on Incrementally Adapted Local Linear Models. - Martin Brablc; Jan Zegklitz; Robert Grepl; Robert Babuska (Complex., 2021)

Benchmarking state-of-the-art symbolic regression algorithms. - Jan Zegklitz; Petr Posík (Genet. Program. Evolvable Mach., 2021)