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

LaTorre, Antonio; Molina, Daniel; Osaba, Eneko; Poyatos, Javier; Del Ser, Javier; [et al.] (Elsevier B.V., 2021-12)
article

Rank Aggregation for Non-stationary Data Streams

Irurozki, Ekhine; Perez, Aritz; Lobo, Jesus; Del Ser, Javier (Springer, 2021-09-11)
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On the post-hoc explainability of deep echo state networks for time series forecasting, image and video classification

Barredo Arrieta, Alejandro; Gil-Lopez, Sergio; Laña, Ibai; Bilbao, Miren Nekane; Del Ser, Javier (Springer, 2021-08-06)
article

Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions

Torre-Bastida, Ana I.; Díaz-de-Arcaya, Josu; Osaba, Eneko; Muhammad, Khan; Camacho, David; [et al.] (Springer, 2021-08-03)
article

Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks

Maciąg, Piotr S.; Kryszkiewicz, Marzena; Bembenik, Robert; L. Lobo, Jesus; Del Ser, Javier (Elsevier Ltd, 2021-07)
article

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

Laña, Ibai; Sanchez-Medina, Javier J.; Vlahogianni, Eleni I.; Del Ser, Javier (Multidisciplinary Digital Publishing Institute (MDPI), 2021-02-05)
article

CURIE: a cellular automaton for concept drift detection

Lobo, Jesus L.; Del Ser, Javier; Osaba, Eneko; Bifet, Albert; Herrera, Francisco (Springer, 2021)
article

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

Rank Aggregation for Non-stationary Data Streams

On the post-hoc explainability of deep echo state networks for time series forecasting, image and video classification

Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions

Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

CURIE: a cellular automaton for concept drift detection

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

Rank Aggregation for Non-stationary Data Streams

On the post-hoc explainability of deep echo state networks for time series forecasting, image and video classification

Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions

Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

CURIE: a cellular automaton for concept drift detection