Farinati, D., & Vanneschi, L. (2025). An Empirical Study of GM4OS for Imbalanced Binary Classification. SN Computer Science, 6(5), Article 510. https://doi.org/10.1007/s42979-025-04048-4 --- Open access funding provided by FCT|FCCN (b-on). This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152 - Centro de Investigação em Gestão de Informaçã...
Rosenfeld, L., Farinati, D., Rasteiro, D., Pietropolli, G., Rebuli, K. B., Silva, S., & Vanneschi, L. (2025). Slim_gsgp: A Python Library for Non-Bloating GSGP. In G. Ochoa (Ed.), GECCO '25: Proceedings of the Genetic and Evolutionary Computation Conference (pp. 1026-1034). ACM - Association for Computing Machinery. https://doi.org/10.1145/3712256.3726398 --- This work was supported by national funds through FC...
ProCAncer-I Consortium, Rodrigues, N. M., Almeida, J. G. D., Verde, A. S. C., Gaivão, A. M., Bireiro, C., Santiago, I., Ip, J., Belião, S., Matos, C., Vanneschi, L., Tsiknakis, M., Marias, K., Regge, D., Silva, S., & Papanikolaou, N. (2025). Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector. Scientific Reports, 15, 1-15. Article 15211. https://doi.o...
Farinati, D., Pietropolli, G., & Vanneschi, L. (2025). A Study on the Dynamics and Effectiveness of the Deflate Geometric Semantic Mutation. IEEE Transactions on Evolutionary Computation. https://doi.org/10.1109/TEVC.2025.3611226 --- %ABS4% --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152 - Centro de Investigação em Gestão de Info...
Rosenfeld, L., & Vanneschi, L. (2025). A Survey on Batch Training in Genetic Programming. Genetic Programming And Evolvable Machines, 26, 1-28. Article 2. https://doi.org/10.1007/s10710-024-09501-6 --- Open access funding provided by FCT|FCCN (b-on). This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Ges...
Cruz, P., Vanneschi, L., & Painho, M. (2025). Understanding Residential Address Patterns in Urban and Rural Areas: A Machine Learning Approach. Transactions in GIS, 29(1), 1-17. Article e70003. https://doi.org/10.1111/tgis.70003 --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project—UIDB/04152/2020—Centro de Investigação em Gestão de Informação (Mag...
Rovito, L., Bonin, L., Farinati, D., Vanneschi, L., Manzoni, L., De Lorenzo, A., & Pietropolli, G. (2025). Semantic-based recombination and mutation in cellular-inspired genetic programming. Genetic Programming And Evolvable Machines, 26(2), Article 27. https://doi.org/10.1007/s10710-025-09524-7 --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project...
Bakurov, I., Muñoz Contreras, J. M., Castelli, M., Rodrigues, N., Silva, S., Trujillo, L., & Vanneschi, L. (2024). Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs. Genetic Programming And Evolvable Machines, 25, 1-29. Article 6. https://doi.org/10.1007/s10710-024-09479-1 --- This work was partially supported by FCT, Portugal, through funding of research units MagIC/NOVA I...
Nadizar, G., Sakallioglu, B., Garrow, F., Silva, S., & Vanneschi, L. (2024). Geometric semantic GP with linear scaling: Darwinian versus Lamarckian evolution. Genetic Programming And Evolvable Machines, 25(2), 1-24. Article 17. https://doi.org/10.1007/s10710-024-09488-0 --- Open access funding provided by Università degli Studi di Trieste within the CRUI-CARE Agreement. This work was partially supported by FCT,...
ProCAncer-I Consortium, Rodrigues, N. M., de Almeida, J. G., Castro Verde, A. S., Gaivão, A. M., Bilreiro, C., Santiago, I., Ip, J., Belião, S., Moreno, R., Matos, C., Vanneschi, L., Tsiknakis, M., Marias, K., Regge, D., Silva, S., & Papanikolaou, N. (2024). Corrigendum to “Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data” [Com...