| Interpretable symbolic regression for data science: Analysis of the 2022 competition FO de França, M Virgolin, M Kommenda, MS Majumder, M Cranmer, ... arXiv preprint arXiv:2304.01117, 2023 | 14 | 2023 |
| Data types as a more ergonomic frontend for grammar-guided genetic programming G Espada, L Ingelse, P Canelas, P Barbosa, A Fonseca Proceedings of the 21st ACM SIGPLAN International Conference on Generative …, 2022 | 12 | 2022 |
| SRBench++: Principled benchmarking of symbolic regression with domain-expert interpretation FO de Franca, M Virgolin, M Kommenda, MS Majumder, M Cranmer, ... IEEE transactions on evolutionary computation, 2024 | 7 | 2024 |
| Personalised gait recognition for people with neurological conditions L Ingelse, D Branco, H Gjoreski, T Guerreiro, R Bouça-Machado, ... Sensors 22 (11), 3980, 2022 | 4 | 2022 |
| Comparing individual representations in grammar-guided genetic programming for glucose prediction in people with diabetes L Ingelse, JI Hidalgo, JM Colmenar, N Lourenço, A Fonseca Proceedings of the Companion Conference on Genetic and Evolutionary …, 2023 | 2 | 2023 |
| Domain-Aware Feature Learning with Grammar-Guided Genetic Programming L Ingelse, A Fonseca European Conference on Genetic Programming (Part of EvoStar), 227-243, 2023 | 2 | 2023 |
| Benchmarking individual representation in grammar-guided genetic programming L Ingelse, G Espada, A Fonseca Technical report, Universidade de Lisboa, 2022 | 2 | 2022 |
| A comparison of representations in grammar-guided genetic programming in the context of glucose prediction in people with diabetes L Ingelse, JI Hidalgo, JM Colmenar, N Lourenço, A Fonseca Genetic Programming and Evolvable Machines 26 (1), 1-25, 2025 | 1 | 2025 |
| Optimization of Feature Learning through Grammar-Guided Genetic Programming LK Ingelse PQDT-Global, 2022 | | 2022 |
