Javier Béjar

发表

Convolutional Neural Networks for Classification of Malware Assembly Code

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

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

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

Social network data analysis for event detection

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

Discovery of Spatio-Temporal Patterns from Location Based Social Networks

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

Nearest-Neighbours for Time Series

Miquel Sànchez-Marrè, Javier Béjar, Juan Manuel Gimeno Illa, 2004, Applied Intelligence.

A distributed control system based on agent architecture for wastewater treatment

Juan A. Baeza, Javier Béjar, Javier Lafuente, 2002 .

Data Preprocessing

Javier Béjar, 2010, Encyclopedia of Machine Learning.

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

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

Agent Strategies on DPB Auction Tournaments

Ulises Cortés, Javier Béjar, 2000, AMEC.

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

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

An Agent Architecture for Supervising a pilot WWTP

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

Wind Energy Forecasting with Neural Networks: A Literature Review

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

Generality-Based Conceptual Clustering with Probabilistic Concepts

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

On the Representativeness of Convolutional Neural Networks Layers

Eduard Ayguadé, Jesús Labarta, Toyotaro Suzumura, 2016, CCIA.

A Data Mining Methodology for Event Analysis in Neurophysiological Signals

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

Reflective Reasoning in a Case-Based Reasoning Agent

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

To Bid or Not To Bid Agent Strategies in Electronic Auction Games

Javier Béjar, Juan A. Rodŕıguez-Aguilar, 2000, AMEC.

Bridging gap between geohydrologic data and Integrated Hydrologic Model: PIHMgis

Andrea Emilio Rizzoli, Miquel Sànchez-Marrè, Javier Béjar, 2008 .

Using the i-walker as a measurement tool for walking behaviour analysis

Javier Béjar, Antonio B. Martínez, Atia Cortés, 2017, REHAB '16.

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.

Using Domain Theory to Bias Classification Processes in Ill-Domains

Ulises Cortés, Javier Béjar, Marta Domingo, 1994 .

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

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

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..

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

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

Extracting Visual Patterns from Deep Learning Representations pdf

Ulises Cortés, Eduard Ayguadé, Jesús Labarta, 2015, ArXiv.

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 .

Spatio-Temporal Gait Analysis Based on Human-Smart Rollator Interaction

Javier Béjar, Antonio B. Martínez, Atia Cortés, 2016, REHAB.

A visual embedding for the unsupervised extraction of abstract semantics

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

Using Kernel Alignment for Feature Selection in Schizophrenia Diagnostic

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..

Predicting Wind Energy Generation with Recurrent Neural Networks

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

Efficient Construction of Comprehensible Hierarchical Clusterings

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

Integrating Declarative Knowledge in Hierarchical Clustering Tasks

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

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

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

Semi-Supervised Clustering

Javier Béjar, 2009, Encyclopedia of Database Systems.

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

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

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

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

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

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

Proceedings of the iEMSs Fourth Biennial Meeting: International Congress on Environmental Modelling and Software (iEMSs 2008)

Andrea Emilio Rizzoli, Miquel Sànchez-Marrè, Giorgio Guariso, 2008 .