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Hernández, A., Amigó, J.M. (2021) «Attention mechanisms and their applications to complex systems», Entropy, 23 (3):1–18, 283

Adrián Hernández and José María Amigó (Universidad Miguel Hernández de Elche)
Abstract: Deep learning models and graphics processing units have completely transformed the field of machine learning. Recurrent neural networks and long short-term memories have been successfully used to model and predict complex systems. However, these classic models do not perform sequential reasoning, a process that […]

Amigó, J.M., Dale, R., Tempesta, P. (2021) «A generalized permutation entropy for noisy dynamics and random processes», Chaos, 31 (1), 013115

José María Amigó, Roberto Dale (Universidad Miguel Hernández de Elche) and Piergiulio Tempesta (Departamento de Física Teórica, Universidad Complutense de Madrid and Instituto de Ciencias Matemáticas)
Abstract: Permutation entropy measures the complexity of a deterministic time series via a data symbolic quantization consisting of rank vectors called ordinal patterns or simply permutations. Reasons for the increasing […]