| 2022 | AAAI | Personalized Public Policy Analysis in Social Sciences Using Causal-Graphical Normalizing Flows. | Sourabh Balgi, Jos M. Pea, Adel Daoud |
| 2016 | UAI | Alternative Markov and Causal Properties for Acyclic Directed Mixed Graphs. | Jos M. Pea |
| 2015 | ECSQARU | Every LWF and AMP Chain Graph Originates from a Set of Causal Models. | Jos M. Pea |
| 2015 | ECSQARU | Factorization, Inference and Parameter Learning in Discrete AMP Chain Graphs. | Jos M. Pea |
| 2015 | UAI | Learning Optimal Chain Graphs with Answer Set Programming. | Dag Sonntag, Matti Jrvisalo, Jos M. Pea, Antti Hyttinen |
| 2014 | AISTATS | An inclusion optimal algorithm for chain graph structure learning. | Jos M. Pea, Dag Sonntag, Jens Dalgaard Nielsen |
| 2013 | ECSQARU | Chain Graph Interpretations and Their Relations. | Dag Sonntag, Jos M. Pea |
| 2007 | UAI | Reading Dependencies from Polytree-Like Bayesian Networks. | Jos M. Pea |
| 2006 | UAI | Identifying the Relevant Nodes Without Learning the Model. | Jos M. Pea, Roland Nilsson, Johan Bjrkegren, Jesper Tegnr |
| 2005 | ECCB | Growing Bayesian network models of gene networks from seed genes. | Jos M. Pea, Johan Bjrkegren, Jesper Tegnr |
| 2005 | ECSQARU | Scalable, Efficient and Correct Learning of Markov Boundaries Under the Faithfulness Assumption. | Jos M. Pea, Johan Bjrkegren, Jesper Tegnr |
| 2005 | IDA | Extending the GA-EDA Hybrid Algorithm to Study Diversification and Intensification in GAs and EDAs. | Vctor Robles, Jos M. Pea, Mara S. Prez, Pilar Herrero, scar Cubo |
| 2004 | CCGRID | Cooperation model of a multiagent parallel file system for clusters. | Mara S. Prez, Alberto Snchez, Vctor Robles, Jos M. Pea, Jemal H. Abawajy |
| 2004 | ICCS | Optimizations Based on Hints in a Parallel File System. | Mara S. Prez, Alberto Snchez, Vctor Robles, Jos M. Pea, Fernando Prez |
| 2004 | ICCSA | Design and Evaluation of an Agent-Based Communication Model for a Parallel File System. | Mara S. Prez, Alberto Snchez, Jemal H. Abawajy, Vctor Robles, Jos M. Pea |
| 2003 | EPIA | Learning Semi Nave Bayes Structures by Estimation of Distribution Algorithms. | Vctor Robles, Pedro Larraaga, Jos M. Pea, Mara S. Prez, Ernestina Menasalvas Ruiz, Vanessa Herves |
| 2003 | ICCS | MOIRAE - An Innovative Component Architecture with Distributed Control Features. | Katia Leal Algara, Jos Herrera, Jos M. Pea, Ernestina Menasalvas Ruiz |
| 2003 | ICCS | A Flexible Multiagent Parallel File System for Clusters. | Mara S. Prez, Jess Carretero, Flix Garca, Jos M. Pea, Vctor Robles |
| 2003 | IDA | Interval Estimation Nave Bayes. | Vctor Robles, Pedro Larraaga, Jos M. Pea, Ernestina Menasalvas Ruiz, Mara S. Prez |
| 2003 | PPAM | Parallel Stochastic Search for Protein Secondary Structure Prediction. | Vctor Robles, Mara S. Prez, Vanessa Herves, Jos M. Pea, Pedro Larraaga |
| 2003 | UAI | On Local Optima in Learning Bayesian Networks. | Jens Dalgaard Nielsen, Toms Kocka, Jos M. Pea |
| 2001 | AISTATS | Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks. | Jos M. Pea, I. Izarzugaza, Jos Antonio Lozano, E. Aldasoro, Pedro Larraaga |
| 2000 | KDD | Data mining to detect abnormal behavior in aerospace data. | Jos M. Pea, Fazel Famili, Sylvain Ltourneau |
| 2000 | UAI | Combinatonal Optimization by Learning and Simulation of Bayesian Networks. | Pedro Larraaga, Ramon Etxeberria, Jos Antonio Lozano, Jos M. Pea |
| 1999 | DaWaK | DAMISYS: An Overview. | M. Covadonga Fernndez, Oscar Delgado, J. Ignacio Lpez, M. Angeles Luna, Jos F. Martnez, J. F. Borja Pardo, Jos M. Pea |
| 1999 | IDA | Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure. | Jos M. Pea, Sylvain Ltourneau, Fazel Famili |