J. Béjar

发表

Integrating Declarative Knowledge in Hierarchical Clustering Tasks

Javier Béjar, Luis Talavera, L. Talavera, 1999, IDA.

EXPLORING PROTEIN PROTEIN DOCKING USING CONVOLUTIONAL NEURAL NETWORKS

J. Béjar, Jairam Venkitachalam, 2017 .

Deep Learning is blowing in the wind. Deep models applied to wind prediction at turbine level

J. Béjar, Jaume Manero, U. Cortés, 2019, Journal of Physics: Conference Series.

Actors and factors - bridging social science findings and urban land use change modeling

J. Comas, G. Guariso, A. Rizzoli, 2008 .

Supraspinal Shaping of Adaptive Transitions in the State of Functional Connectivity Between Segmentally Distributed Dorsal Horn Neuronal Populations in Response to Nociception and Antinociception

P. Rudomín, S. Glusman, Mario Martín, 2019, Frontiers in Systems Neuroscience.

Development of a Web based Decision Support System for trans-boundary environmental risk assessment and management

A. Rizzoli, M. Sànchez-Marrè, J. Béjar, 2008 .

A Design for Framework-Independent Model Components of Biophysical Systems

J. Comas, J. Béjar, 2008 .

Assessing Falling Risk in Elderly with the Ten Meter Walking Test: A Machine Learning Approach

Ulises Cortés, Javier Béjar, Cristian Barrué, 2016, CCIA.

Using Domain Theory to Bias Classification Processes in Ill-Domains

Ulises Cortés, Javier Béjar, Marta Domingo, 1994 .

Using Kernel Alignment for Feature Selection in Schizophrenia Diagnostic

Ulises Cortés, Javier Béjar, Gennaro Esposito, 2015, CCIA.

A Data Mining Methodology for Event Analysis in Neurophysiological Signals

Ulises Cortés, Javier Béjar, Gennaro Esposito, 2015, CCIA.

A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in neuronal connectivity induced by nociceptive stimulation

Ulises Cortés, Javier Béjar, Gennaro Esposito, 2015, Front. Neuroinform..

Convolutional Neural Networks for Classification of Malware Assembly Code

Daniel Gibert, Javier Béjar, Carles Mateu, 2017, CCIA.

An Agent Architecture for Supervising a pilot WWTP

Juan A. Baeza, Javier Béjar, Javier Lafuente, 1999 .

Clustering algorithm for determining community structure in large networks.

Javier Béjar, Jordi Delgado, Josep M Pujol, 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

Kernel alignment for identifying objective criteria from brain MEG recordings in schizophrenia

Ulises Cortés, Javier Béjar, Gennaro Esposito, 2017, Pattern Recognit. Lett..

A visual embedding for the unsupervised extraction of abstract semantics

Ulises Cortés, Eduard Ayguadé, Jesús Labarta, 2015, Cognitive Systems Research.

Efficient Construction of Comprehensible Hierarchical Clusterings

Javier Béjar, Luis Talavera, J. Béjar, 1998, PKDD.

Reflective Reasoning in a Case-Based Reasoning Agent

Miquel Sànchez-Marrè, Ignasi Rodríguez-Roda, Javier Béjar, 1999, Collaboration between Human and Artificial Societies.

Semi-Supervised Clustering

J. Béjar, 2021, Encyclopedia of Database Systems.

“Dust in the Wind...”, Deep Learning Application to Wind Energy Time Series Forecasting

Javier Béjar, Jaume Manero, J. Béjar, 2019, Energies.

Discovery of spatio-temporal patterns from location-based social networks

Javier Vázquez-Salceda, Javier Béjar, Sergio Álvarez-Napagao, 2016, J. Exp. Theor. Artif. Intell..

Discovery of Spatio-Temporal Patterns from Location Based Social Networks

Javier Vázquez-Salceda, Javier Béjar, Sergio Álvarez-Napagao, 2014, CCIA.

Generality-Based Conceptual Clustering with Probabilistic Concepts

Javier Béjar, Luis Talavera, J. Béjar, 2001, IEEE Trans. Pattern Anal. Mach. Intell..

Wind Energy Forecasting with Neural Networks: A Literature Review

Ulises Cortés, Javier Béjar, Jaume Manero, 2018, Computación y Sistemas.

Concept Formation in WWTP by Means of Classification Techniques: A Compared Study

Miquel Sànchez-Marrè, Ulises Cortés, Javier Béjar, 1997, Applied Intelligence.

Predicting Wind Energy Generation with Recurrent Neural Networks

Ulises Cortés, Javier Béjar, Jaume Manero, 2018, IDEAL.

Large scale prediction of sick leave duration with nonlinear survival analysis algorithms

D. García-Gasulla, J. Béjar, Armand Vilalta, 2022, Expert Syst. Appl..

Forecastability Measures that Describe the Complexity of a Site for Deep Learning Wind Predictions

Javier Béjar, Jaume Manero, J. Béjar, 2021, Supercomput. Front. Innov..

Go with the Flow: Recurrent Networks for Wind Time Series Multi-Step Forecasting

Ulises Cortés, Javier Béjar, Jaume Manero, 2018, CCIA.

Automatic classification of gait patterns using a smart rollator and the BOSS model

Ulises Cortés, Javier Béjar, Atia Cortés, 2018, PETRA.

Social network data analysis for event detection

Javier Vázquez-Salceda, Javier Béjar, Sergio Álvarez-Napagao, 2014, ECAI.

An Approach to Gait Analysis from Human-Rollator Interaction: The i-Walker

Javier Béjar, Antonio B. Martínez, Atia Cortés, 2018, CCIA.

Improving Knowledge Discovery Using Domain Knowledge in Unsupervised Learning

Javier Béjar, J. Béjar, 2000, ECML.

Experiments with Domain Knowledge in Unsupervised Learning: Using and Revising Theories

Ulises Cortés, Javier Béjar, J. Béjar, 1998 .

Supraspinal modulation of neuronal synchronization by nociceptive stimulation induces an enduring reorganization of dorsal horn neuronal connectivity

P. Rudomín, S. Glusman, J. Béjar, 2018, The Journal of physiology.

Markovian Analysis of the Sequential Behavior of the Spontaneous Spinal Cord Dorsum Potentials Induced by Acute Nociceptive Stimulation in the Anesthetized Cat

Ulises Cortés, Javier Béjar, Gennaro Esposito, 2017, Front. Comput. Neurosci..