Publikationen, an denen er mitarbeitet Javier Poyatos (8)

2024

  1. General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance

    Information Fusion, Vol. 103

2023

  1. EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks

    Neural Networks, Vol. 158, pp. 59-82

  2. Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness

    Applied Soft Computing, Vol. 147

2022

  1. Optimización inspirada en la naturaleza y en la biología: lo bueno, lo malo, lo feo y lo esperanzador

    Revista DYNA, Vol. 97, Núm. 2, pp. 114-117

2021

  1. A prescription of methodological guidelines for comparing bio-inspired optimization algorithms

    Swarm and Evolutionary Computation, Vol. 67

  2. Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges

    Information Fusion, Vol. 67, pp. 161-194

  3. More is not Always Better: Insights from a Massive Comparison of Meta-heuristic Algorithms over Real-Parameter Optimization Problems

    2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings

2020

  1. Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations

    Cognitive Computation, Vol. 12, Núm. 5, pp. 897-939