default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDGenetic Programming and Evolvable Machines, Volume 26
Volume 26, Number 1, June 2025
- Renske Vroomans:
Review: "Computational evolution of neural and morphological development", Yaochu Jin, ISBN 978-981-99-1853-9, Springer, 2023. 1 - Liah Rosenfeld, Leonardo Vanneschi:
A survey on batch training in genetic programming. 2 - Jorge Cano
, José Ignacio Hidalgo, Oscar Garnica:
Hardware real-time individualised blood glucose predictor generator based on grammars and cartesian genetic programming. 3 - Ulviya Abdulkarimova, Rodrigo Abarca-del-Río, Pierre Collet:
Harnessing evolutionary algorithms for enhanced characterization of ENSO events. 4 - Leon Ingelse, José Ignacio Hidalgo, J. Manuel Colmenar, Nuno Lourenço, Alcides Fonseca:
A comparison of representations in grammar-guided genetic programming in the context of glucose prediction in people with diabetes. 5 - Jose Manuel Muñoz Contreras, Leonardo Trujillo, Daniel E. Hernández, Luis A. Cardenas Florido:
Benchmarking GSGP: Still competitive 10 years later? 6 - Alberto Tonda:
Review of PySR: high-performance symbolic regression in Python and Julia. 7 - Christopher Crary, Wesley Piard, Greg Stitt, Benjamin M. Hicks, Caleb Bean, Bogdan Burlacu, Wolfgang Banzhaf:
Using FPGA devices to accelerate the evaluation phase of tree-based genetic programming: an extended analysis. 8 - Eric Medvet, Erica Salvato:
The science of soft robots, Koichi Suzumori, Kenjiro Fukuda, Ryuma Niiyama, and Kohei Nakajima: ISBN 978-9811951732, Springer 2023. 9 - Saltuk Bugra Selçuklu:
"Machine learning assisted evolutionary multi- and many-objective optimization" by Dhish Kumar Saxena, Sukrit Mittal, Kalyanmoy Deb, and Erik D. Goodman, ISBN 978-981-99-2095-2, Springer, 2024. 10 - Alessandro Ferreira Leite, Marc Schoenauer:
Memetic semantic boosting for symbolic regression. 11 - Maximilian Reissmann, Yuan Fang, Andrew S. H. Ooi, Richard D. Sandberg:
Constraining genetic symbolic regression via semantic backpropagation. 12 - Gisele L. Pappa, Mario Giacobini, Ting Hu, Domagoj Jakobovic:
Editorial introduction for the special issue on highlights of genetic programming 2023 events. 13 - Mohammad Reza Keyvanpour, Zahra Karimi Zandian, Elham Sodagari:
RSCID: requirements selection considering interactions and dependencies. 14 - William G. La Cava:
A review of "Symbolic Regression" by Gabriel Kronberger, Bogdan Burlacu, Michael Kommenda, Stephan M. Winkler, and Michael Affenzeller, ISBN 978-1-138-05481-3, 2024, CRC Press. 15 - Alberto Moraglio, Krzysztof Krawiec, Colin G. Johnson:
Editorial introduction to the special issue for the tenth anniversary of geometric semantic genetic programming. 16
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-04-08 20:49 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
