- Bojan Mihaljevic, Pedro Larranaga and Concha Bielza, Comparing the electophysiology and morphology of human and mouse layer 2/3 pyramidal neurons with Bayesian networks,
- C Bielza, P Larrañaga, Data-driven computational neuroscience: machine learning and statistical models, Cambridge University Press
- Atienza, D., C. Bielza, J. Díaz-Rozo, and P. Larrañaga, “Efficient anomaly detection in a laser surface heat treatment process by tracking the laser spot”, IEEE/ASME Transactions on Mechatronics, accepted, 2020.
- Córdoba-Sánchez, I., C. Bielza, P. Larrañaga, and G. Varando, “Sparse Cholesky Covariance Parametrization for Recovering Latent Structure in Ordered Data”, IEEE Access, vol. 8, pp. 154614 – 154624, 2020.
- Córdoba-Sánchez, I., C. Bielza, and P. Larrañaga, “A review of Gaussian Markov models for conditional independence“, Journal of Statistical Planning and Inference, vol. 206, pp. 127-144, 2020. BibTex
- Córdoba-Sánchez, I., G. Varando, C. Bielza, and P. Larrañaga, “On generating random Gaussian graphical models“, International Journal of Approximate Reasoning, vol. 125, pp. 240 – 250, 2020. BibTex
- Díaz-Rozo, J., C. Bielza, and P.. Larrañaga, “Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering”, Engineering Applications of Artificial Intelligence, vol. 89, pp. 103434, mar. 2020. BibTex
- Gil-Begue, S., C. Bielza, and P. Larrañaga, “Multi-dimensional Bayesian network classifiers: A survey”, Artificial Intelligence Review, vol. accepted, 2020. BibTex
- Michiels, M., P. Larrañaga, and C. Bielza, “BayeSuites: An open web framework for massive Bayesian networks focused on neuroscience”, Neurocomputing, vol. 428, pp. 166 – 181, 2020. BibTex
- Mihaljevic, B., P.. Larrañaga, R. Benavides-Piccione, J. DeFelipe, and C. Bielza, “Comparing basal dendrite branches in human and mouse hippocampal CA1 pyramidal neurons with Bayesian networks“, Scientific Reports, accepted, 2020. Scientific reports 10 (1), 1-13
- Rodriguez-Sanchez, F., P.. Larrañaga, and C. Bielza, “Incremental Learning of Latent Forests“, IEEE Access, 2020. IEEE Access 8, 224420-224432
- Yuste, R., E. Lein, M. Hawrylycz, and C. Convention Group, “A community-based transcriptomics classification and nomenclature of neocortical cell types“, Nature Neuroscience, , vol. 23, pp. 1456–1468, 08/2020. BibTex
