New Probabilistic, Dynamic Multi-Method Ensembles for Optimization Based on the CRO-SL - Pérez-Aracil, J.; Camacho-Gómez, C.; Lorente-Ramos, E.; Marina, C.M.; Cornejo-Bueno, L.M.; Salcedo-Sanz, S. (Mathematics, 2023)

Go-around occurrence prediction with rule-induction, rule evolution and Machine Learning algorithms - Marina, C.M.; Pérez-Aracil, J.; Lorente-Ramos, E.; Casanova-Mateo, C.; Salcedo-Sanz, S. (Advanced Engineering Informatics, 2025)

Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction - Marina, C.M.; Lorente-Ramos, E.; Ayllón-Gavilán, R.; Gutiérrez, P.A.; Pérez-Aracil, J.; Salcedo-Sanz, S. (Lecture Notes In Computer Science, 2024)

TensorCRO: A TensorFlow-based implementation of a multi-method ensemble for optimization - Palomo-Alonso, A.; Costa, V.G.; Moreno-Saavedra, L.M.; Lorente-Ramos, E.; Pérez-Aracil, J.; Pedreira, C.E.; Salcedo-Sanz, S. (Expert Systems, 2024)

Machine learning as alternative strategy for the numerical prediction of the shear response in reinforced and prestressed concrete beams - Hernández-Díaz, A.M.; Pérez-Aracil, J.; Lorente-Ramos, E.; Marina, C.M.; Peláez-Rodríguez, C.; Salcedo-Sanz, S. (Results In Engineering, 2024)

Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection - Pérez-Aracil,J.; Peláez-Rodríguez,C.; McAdam,R.; Squintu,A.; Marina,C.M.; Lorente-Ramos,E.; Luther,N.; Torralba,V.; Scoccimarro,E.; Cavicchia,L.; Giuliani,M.; Zorita,E.; et al. (Weather and Climate Extremes, 2025)

Detection and attribution of heat waves with the Multivariate Autoencoder Flow-Analogue Method (MvAE-AM) - Marina,C.M.; Pérez-Aracil,J.; McAdam,R.; Lorente-Ramos,E.; Luther,N.; Zorita,E.; Scoccimarro,E.; Luterbacher,J.; Xoplaki,E.; Salcedo-Sanz,S. (Atmospheric Research, 2026)

An improved machine learning strategy for shear analysis in structural concrete based on the Newton's method and the solvability region of the steel constitutive model - Lorente-Ramos,E.; Hernández-Díaz,A.M.; Pérez-Aracil,J.; Salcedo-Sanz,S. (Journal of Computational Physics, 2025)