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Javier Bejar
Javier Bejar
Associate Professor of Artificial Intelligence, Universitat Politècnica de Catalunya
Verifisert e-postadresse på cs.upc.edu
Tittel
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Sitert av
År
Clustering algorithm for determining community structure in large networks
JM Pujol, J Béjar, J Delgado
Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 74 (1 …, 2006
1762006
Generality-based conceptual clustering with probabilistic concepts
L Talavera, J Béjar
IEEE Transactions on pattern analysis and machine intelligence 23 (2), 196-206, 2001
822001
Aprendizaje automático
A Moreno, E Armengol, J Béjar Alonso, LA Belanche Muñoz, ...
Edicions UPC, 1994
821994
Concept formation in WWTP by means of classification techniques: a compared study
M Sànchez, U Cortés, J Béjar, JD Grácia, J Lafuente, M Poch
Applied Intelligence 7 (2), 147-165, 1997
751997
DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision
M Sànchez, U Cortés, J Lafuente, IR Roda, M Poch
Artificial Intelligence in Engineering 10 (3), 275-285, 1996
591996
Neuropsychological impairment in post-COVID condition individuals with and without cognitive complaints
M Ariza, N Cano, B Segura, A Adan, N Bargalló, X Caldú, A Campabadal, ...
Frontiers in aging neuroscience 14, 1029842, 2022
572022
Integrating declarative knowledge in hierarchical clustering tasks
L Talavera, J Béjar
Advances in Intelligent Data Analysis, 211-222, 1999
551999
COVID-19 severity is related to poor executive function in people with post-COVID conditions
M Ariza, N Cano, B Segura, A Adan, N Bargalló, X Caldú, A Campabadal, ...
Journal of Neurology 270 (5), 2392-2408, 2023
472023
K-means vs Mini Batch K-means: a comparison
J Béjar Alonso
452013
Wind energy forecasting with neural networks: A literature review
J Manero, J Béjar, U Cortés
Computación y Sistemas 22 (4), 1085-1098, 2018
432018
“Dust in the wind...”, deep learning application to wind energy time series forecasting
J Manero, J Béjar, U Cortés
Energies 12 (12), 2385, 2019
402019
Convolutional neural networks for classification of malware assembly code
D Gibert, J Béjar, C Mateu, J Planes, D Solis, R Vicens
Recent Advances in Artificial Intelligence Research and Development, 221-226, 2017
352017
Discovery of Spatio-Temporal Patterns from Location Based Social Networks.
J Bejar, S Álvarez-Napagao, D Garcia-Gasulla, I Gómez-Sebastià, L Oliva, ...
CCIA, 126-135, 2014
262014
LINNEO+: Herramienta para la adquisición de conocimiento y generación de reglas de clasificación en dominios poco estructurados
J Béjar, U Cortés
Actas del III Congreso Iberoamericano de Inteligencia Artificial (IBERAMIA92), 1992
251992
A distributed control system based on agent architecture for wastewater treatment
J Baeza, D Gabriel, J Béjar, J Lafuente
Computer‐Aided Civil and Infrastructure Engineering 17 (2), 93-103, 2002
242002
K-means vs mini batch k-means: A comparison
J Béjar
KEMLG-Grup d’Enginyeria del Coneixement i Aprenentatge Automàtic-Reports de …, 2013
232013
Nearest-neighbours for time series
JMG Illa, JB Alonso, MS Marré
Applied Intelligence 20 (1), 21-35, 2004
232004
Supraspinal modulation of neuronal synchronization by nociceptive stimulation induces an enduring reorganization of dorsal horn neuronal connectivity
E Contreras‐Hernández, D Chávez, E Hernández, E Velázquez, P Reyes, ...
The Journal of Physiology 596 (9), 1747-1776, 2018
172018
A visual embedding for the unsupervised extraction of abstract semantics
D Garcia-Gasulla, E Ayguadé, J Labarta, J Béjar, U Cortés, T Suzumura, ...
Cognitive Systems Research 42, 73-81, 2017
162017
A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in …
M Martin, E Contreras-Hernández, J Béjar, G Esposito, D Chávez, ...
Frontiers in neuroinformatics 9, 21, 2015
142015
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Artikler 1–20