New Probabilistic-Dynamic Multi-Method Ensembles for Optimization based on the CRO-SL. - Jorge Pérez-Aracil; Carlos Camacho-Gómez; Eugenio Lorente-Ramos; Cosmin Madalin Marina; Sancho Salcedo-Sanz (CoRR, 2022)

Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction. - Cosmin Madalin Marina; Eugenio Lorente-Ramos; Rafael Ayllón-Gavilán; Pedro Antonio Gutiérrez; Jorge Pérez-Aracil; Sancho Salcedo-Sanz (CAEPIA, 2024)

Machine Learning as Applied to Shape Parameterization of Submerged Arch Structures. - Waldemar Hugo LLamosas-Mayca; Eugenio Lorente-Ramos; Jorge Pérez-Aracil; Alejandro M. Hernández-Díaz; Manuel D. García-Román; Sancho Salcedo-Sanz (IWINAC (2), 2024)

Identifying Key Drivers of Heatwaves: A Novel Spatio-Temporal Framework for Extreme Event Detection. - Jorge Pérez-Aracil; César Peláez-Rodríguez; Ronan McAdam; Antonello Squintu; Cosmin M. Marina; Eugenio Lorente-Ramos; Niklas Luther; Veronica Torralba; Enrico Scoccimarro; Leone Cavicchia; Matteo Giuliani; Eduardo Zorita; et al. (CoRR, 2024)

TensorCRO: A TensorFlow-based implementation of a multi-method ensemble for optimization. - Alberto Palomo-Alonso; Vinícius G. Costa; Luis M. Moreno-Saavedra; Eugenio Lorente-Ramos; Jorge Pérez-Aracil; Carlos Eduardo Pedreira; Sancho Salcedo-Sanz (Expert Syst. J. Knowl. Eng., 2024)

Go-around occurrence prediction with rule-induction, rule evolution and Machine Learning algorithms. - Cosmin Madalin Marina; Jorge Pérez-Aracil; Eugenio Lorente-Ramos; Carlos Casanova-Mateo; Sancho Salcedo-Sanz (Adv. Eng. Informatics, 2025)