Improving Inverse Control on Real Time by Means of Neural Networks. - D. Barrios; Inés María Galván; P. Jsasi; J. Ríos (ICONIP (2), 1997)

Nuevos modelos de redes de neuronas artificiales para simulación y control desistemas dinámicos. - Inés María Galván (1997)

Grammars and cellular automata for evolving neural networks architectures. - José M. Molina 001; Inés María Galván; Pedro Isasi; Araceli Sanchis (SMC, 2000)

Sistema Multiagente para el diseño de Redes de Neuronas de Base Radial Óptimas. - José María Valls; José M. Molina 001; Inés María Galván (Inteligencia Artif., 2000)

Deferring the Learning for Better Generalization in Radial Basis Neural Networks. - José María Valls; Pedro Isasi; Inés María Galván (ICANN, 2001)

Evolutionary Cellular Configurations for Designing Feed-Forward Neural Networks Architectures. - Germán Gutiérrez; Pedro Isasi; José M. Molina 001; Araceli Sanchis; Inés María Galván (IWANN (1), 2001)

Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks Using a Multi-Agent System. - José M. Molina 001; Inés María Galván; José María Valls; Andrés Leal (Comput. Artif. Intell., 2001)

A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks. - Inés María Galván; Pedro Isasi; Ricardo Aler; José María Valls (Int. J. Neural Syst., 2001)

Multi-step Learning Rule for Recurrent Neural Models: An Application to Time Series Forecasting. - Inés María Galván; Pedro Isasi (Neural Process. Lett., 2001)

Generative capacities of grammars codification for evolution of NN architectures. - M. A. Guinea; Germán Gutiérrez; Inés María Galván; Araceli Sanchis; José M. Molina 001 (IEEE Congress on Evolutionary Computation, 2002)

Generative Capacities of Cellular Automata Codification for Evolution of NN Codification. - Germán Gutiérrez; Inés María Galván; José M. Molina 001; Araceli Sanchis (ICANN, 2002)

Modified Self-organizing Maps for Line Extraction in Digitized Text Documents. - Juan Manuel Alonso-Weber; Inés María Galván; Araceli Sanchis de Miguel (Applied Informatics, 2003)

How the Selection of Training Patterns can Improve the Generalization Capability in Radial Basis Neural Networks. - José María Valls; Inés María Galván; Pedro Isasi (Applied Informatics, 2003)

A Better Selection of Patterns in Lazy Learning Radial Basis Neural Networks. - Pedro Isasi; José María Valls; Inés María Galván (IWANN (1), 2003)

Studying the capacity of cellular encoding to generate feedforward neural network topologies. - Germán Gutiérrez; Inés María Galván; José M. Molina 001; Araceli Sanchis (IJCNN, 2004)

Lazy Learning in Radial Basis Neural Networks: A Way of Achieving More Accurate Models. - José María Valls; Inés María Galván; Pedro Isasi (Neural Process. Lett., 2004)

A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm. - Alejandro Cervantes; Inés María Galván; Pedro Isasi (Congress on Evolutionary Computation, 2005)

Neural Networks and Spectral Feature Selection for Retrieval of Hot Gases Temperature Profiles. - Esteban García-Cuesta; Inés María Galván; Antonio J. de Castro (CIMCA/IAWTIC, 2005)

A First Attempt at Constructing Genetic Programming Expressions for EEG Classification. - César Estébanez; José María Valls; Ricardo Aler; Inés María Galván (ICANN (1), 2005)

Non-Direct Encoding Method Based on Cellular Automata to Design Neural Network Architectures. - Germán Gutiérrez; Araceli Sanchis; Pedro Isasi Viñuela; José M. Molina 001; Inés María Galván (Comput. Artif. Intell., 2005)

Lazy Training of Radial Basis Neural Networks. - José María Valls; Inés María Galván; Pedro Isasi (ICANN (1), 2006)

Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles. - Esteban García-Cuesta; Inés María Galván; Antonio J. de Castro (IDEAL, 2006)

Improving the Generalization Ability of RBNN Using a Selective Strategy Based on the Gaussian Kernel Function. - José María Valls; Inés María Galván; Pedro Isasi Viñuela (Comput. Artif. Intell., 2006)

An Adaptive Michigan Approach PSO for Nearest Prototype Classification. - Alejandro Cervantes; Inés María Galván; Pedro Isasi (IWINAC (2), 2007)

Building Nearest Prototype Classifiers Using a Michigan Approach PSO. - Alejandro Cervantes; Inés María Galván; Pedro Isasi (SIS, 2007)

LRBNN: A Lazy Radial Basis Neural Network model. - José María Valls; Inés María Galván; Pedro Isasi (AI Commun., 2007)

Multilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem. - Esteban García-Cuesta; Inés María Galván; Antonio J. de Castro (Eng. Appl. Artif. Intell., 2008)

Learning radial basis neural networks in a lazy way: A comparative study. - José María Valls; Inés María Galván; Pedro Isasi Viñuela (Neurocomputing, 2008)

Improving Classification for Brain Computer Interfaces using Transitions and a Moving Window. - Ricardo Aler; Inés María Galván; José María Valls (BIOSIGNALS, 2009)

Transition Detection for Brain Computer Interface Classification. - Ricardo Aler; Inés María Galván; José María Valls (BIOSTEC (Selected Papers), 2009)

Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms. - Carlos Segura; Alejandro Cervantes; Antonio J. Nebro; María Dolores Jaraíz-Simón; Eduardo Segredo; Sandra García-Rodríguez; Francisco Luna 001; Juan Antonio Gómez Pulido; Gara Miranda; Cristóbal Luque; Enrique Alba 001; Miguel Ángel Vega Rodríguez; et al. (EMO, 2009)

Discriminant Regression Analysis to Find Homogeneous Structures. - Esteban García-Cuesta; Inés María Galván; Antonio J. de Castro (IDEAL, 2009)

A Lazy Approach for Machine Learning Algorithms. - Inés María Galván; José María Valls; Nicolas Lecomte; Pedro Isasi (AIAI, 2009)

Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks. - Sandra García-Rodríguez; Cristóbal Luque; Alejandro Cervantes; Inés María Galván (IWANN (1), 2009)

Supervised clustering via principal component analysis in a retrieval application. - Esteban García-Cuesta; Inés María Galván; Antonio J. de Castro (KDD Workshop on Knowledge Discovery from Sensor Data, 2009)

Michigan Particle Swarm Optimization for Prototype Reduction in Classification Problems. - Alejandro Cervantes; Inés María Galván; Pedro Isasi Viñuela (New Gener. Comput., 2009)

AMPSO: A New Particle Swarm Method for Nearest Neighborhood Classification. - Alejandro Cervantes; Inés María Galván; Pedro Isasi (IEEE Trans. Syst. Man Cybern. Part B, 2009)

Evolving spatial and frequency selection filters for Brain-Computer Interfaces. - Ricardo Aler; Inés María Galván; José María Valls (IEEE Congress on Evolutionary Computation, 2010)

Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data. - Sandra García-Rodríguez; Ricardo Aler; Inés María Galván (ICANN (1), 2010)

Portfolio Optimization Using SPEA2 with Resampling. - Sandra García-Rodríguez; David Quintana; Inés María Galván; Pedro Isasi (IDEAL, 2011)

A lazy learning approach for building classification models. - Inés María Galván; José María Valls; Miguel García; Pedro Isasi (Int. J. Intell. Syst., 2011)

Recursive Discriminant Regression Analysis to Find Homogeneous Groups. - Esteban García-Cuesta; Inés María Galván; Antonio J. de Castro (Int. J. Neural Syst., 2011)

Time-stamped resampling for robust evolutionary portfolio optimization. - Sandra García-Rodríguez; David Quintana; Inés María Galván; Pedro Isasi (Expert Syst. Appl., 2012)

Applying evolution strategies to preprocessing EEG signals for brain-computer interfaces. - Ricardo Aler; Inés María Galván; José María Valls (Inf. Sci., 2012)

Multiobjective Algorithms with Resampling for Portfolio Optimization. - Sandra García-Rodríguez; David Quintana; Inés María Galván; Pedro Isasi (Comput. Informatics, 2013)

A Study of Machine Learning Techniques for Daily Solar Energy Forecasting Using Numerical Weather Models. - Ricardo Aler; Ricardo Martín; José María Valls; Inés María Galván (IDC, 2014)

Extended mean-variance model for reliable evolutionary portfolio optimization. - Sandra García-Rodríguez; David Quintana; Inés María Galván; Pedro Isasi (AI Commun., 2014)

Optimizing the number of electrodes and spatial filters for Brain-Computer Interfaces by means of an evolutionary multi-objective approach. - Ricardo Aler; Inés María Galván (Expert Syst. Appl., 2015)

Machine learning techniques for daily solar energy prediction and interpolation using numerical weather models. - R. Martin; Ricardo Aler; José María Valls; Inés María Galván (Concurr. Comput. Pract. Exp., 2016)

A Study on Feature Selection Methods for Wind Energy Prediction. - Rubén Martín-Vázquez; Ricardo Aler; Inés María Galván (IWANN (1), 2017)

Multi-objective evolutionary optimization of prediction intervals for solar energy forecasting with neural networks. - Inés María Galván; José María Valls; Alejandro Cervantes; Ricardo Aler (Inf. Sci., 2017)

Predicting Global Irradiance Combining Forecasting Models Through Machine Learning. - Javier Huertas-Tato; Ricardo Aler; Francisco J. Rodríguez-Benítez; Clara Arbizu-Barrena; David Pozo-Vázquez; Inés María Galván (HAIS, 2018)

Studying the Effect of Measured Solar Power on Evolutionary Multi-objective Prediction Intervals. - Rubén Martín-Vázquez; Javier Huertas-Tato; Ricardo Aler; Inés María Galván (IDEAL (2), 2018)

Wind Energy Forecasting at Different Time Horizons with Individual and Global Models. - Rubén Martín-Vázquez; Ricardo Aler; Inés María Galván (AIAI, 2018)

A Comparative Study of Classical Clustering Method and Cuckoo Search Approach for Satellite Image Clustering: Application to Water Body Extraction. - Kaouter Labed; Fizazi Hadria; Habib Mahi; Inés María Galván (Appl. Artif. Intell., 2018)

A filter attribute selection method based on local reliable information. - Ricardo Martín; Ricardo Aler; Inés María Galván (Appl. Intell., 2018)

Evolutionary-based prediction interval estimation by blending solar radiation forecasting models using meteorological weather types. - Inés María Galván; Javier Huertas-Tato; Francisco J. Rodríguez-Benítez; Clara Arbizu-Barrena; David Pozo-Vázquez; Ricardo Aler (Appl. Soft Comput., 2021)

Supervised data transformation and dimensionality reduction with a 3-layer multi-layer perceptron for classification problems. - José María Valls; Ricardo Aler; Inés María Galván; David Camacho (J. Ambient Intell. Humaniz. Comput., 2021)

Direct estimation of prediction intervals for solar and wind regional energy forecasting with deep neural networks. - Antonio Alcántara; Inés María Galván; Ricardo Aler (Eng. Appl. Artif. Intell., 2022)

Using a Multi-view Convolutional Neural Network to monitor solar irradiance. - Javier Huertas-Tato; Inés María Galván; Ricardo Aler; Francisco J. Rodríguez-Benítez; David Pozo-Vázquez (Neural Comput. Appl., 2022)

Pareto Optimal Prediction Intervals with Hypernetworks. - Antonio Alcántara; Inés María Galván; Ricardo Aler (Appl. Soft Comput., 2023)

Deep neural networks for the quantile estimation of regional renewable energy production. - Antonio Alcántara; Inés María Galván; Ricardo Aler (Appl. Intell., 2023)

Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques. - Miguel López-Cuesta; Ricardo Aler; Inés María Galván; Francisco J. Rodríguez-Benítez; David Pozo-Vázquez (Remote. Sens., 2023)

A combination of supervised dimensionality reduction and learning methods to forecast solar radiation. - Esteban García-Cuesta; Ricardo Aler; David Pozo-Vázquez; Inés María Galván (Appl. Intell., 2023)

Artificial intelligence for identification of candidates for device-aided therapy in Parkinson's disease: DELIST-PD study. - Eric Freire-Álvarez; Inés Legarda Ramírez; Rocio García-Ramos; Fátima Carrillo; Diego Santos-García; Juan Carlos Gómez-Esteban; Juan Carlos Martínez-Castrillo; Irene Martínez-Torres; Carlos J. Madrid-Navarro; María José Pérez-Navarro; Fuensanta Valero-García; Bárbara Vives-Pastor; et al. (Comput. Biol. Medicine, 2025)