Francisco J. Baldán

According to our database, Francisco J. Baldán authored at least 12 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

MoTime: A Dataset Suite for Multimodal Time Series Forecasting.

Xin Zhou, Weiqing Wang, Francisco J. Baldán, Wray L. Buntine, Christoph Bergmeir

CoRR, May, 2025

Benchmarking Anomaly Detection Methods: Insights From the UCR Time Series Anomaly Archive.

Francisco J. Baldán, Diego García-Gil

Expert Syst. J. Knowl. Eng., February, 2025

Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems.

Francisco J. Baldán, Diego García-Gil, Carlos Fernandez-Basso

Comput., 2025

2024

Natural noise management in collaborative recommender systems over time-related information.

Francisco J. Baldán, Raciel Yera, Luis Martínez

J. Supercomput., November, 2024

Time series features and fuzzy memberships combination for time series classification.

Francisco J. Baldán, Luis Martínez

Neurocomputing, 2024

2023

Complexity measures and features for times series classification.

Francisco J. Baldán, José Manuel Benítez

Expert Syst. Appl., 2023

2022

Semantic of Cloud Computing services for Time Series workflows.

Manuel Parra-Royon, Francisco J. Baldán, Ghislain Atemezing, José Manuel Benítez

CoRR, 2022

2021

Multivariate times series classification through an interpretable representation.

Francisco J. Baldán, José Manuel Benítez

Inf. Sci., 2021

SCMFTS: Scalable and Distributed Complexity Measures and Features for Univariate and Multivariate Time Series in Big Data Environments.

Francisco J. Baldán, Daniel Peralta, Yvan Saeys, José Manuel Benítez

Int. J. Comput. Intell. Syst., 2021

2020

Multivariable times series classification through an interpretable representation.

Francisco J. Baldán, José Manuel Benítez

CoRR, 2020

2019

Distributed FastShapelet Transform: a Big Data time series classification algorithm.

Francisco J. Baldán, José Manuel Benítez

Inf. Sci., 2019

2018

A Forecasting Methodology for Workload Forecasting in Cloud Systems.

Francisco J. Baldán, Sergio Ramírez-Gallego, Christoph Bergmeir, Francisco Herrera, José Manuel Benítez

IEEE Trans. Cloud Comput., 2018