Gherardo Varando
Gherardo Varando
Department of Mathematical Sciences, Univeristy of Copenhagen
Dirección de correo verificada de math.ku.dk - Página principal
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A survey on multi‐output regression
H Borchani, G Varando, C Bielza, P Larrañaga
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 5 (5 …, 2015
2322015
Decision boundary for discrete Bayesian network classifiers
G Varando, C Bielza, P Larranaga
The Journal of Machine Learning Research 16 (1), 2725-2749, 2015
222015
Expressive power of binary relevance and chain classifiers based on Bayesian networks for multi-label classification
G Varando, C Bielza, P Larranaga
European Workshop on Probabilistic Graphical Models, 519-534, 2014
102014
Decision functions for chain classifiers based on Bayesian networks for multi-label classification
G Varando, C Bielza, P Larrañaga
International Journal of Approximate Reasoning 68, 164-178, 2016
92016
Conditional density approximations with mixtures of polynomials
G Varando, PL López‐Cruz, TD Nielsen, P Larranaga, C Bielza
International Journal of Intelligent Systems 30 (3), 236-264, 2015
52015
Graphical continuous Lyapunov models
G Varando, NR Hansen
arXiv preprint arXiv:2005.10483, 2020
22020
MultiMap: A tool to automatically extract and analyse spatial microscopic data from large stacks of confocal microscopy images
G Varando, R Benavides-Piccione, A Muñoz, A Kastanauskaite, C Bielza, ...
Frontiers in neuroanatomy 12, 37, 2018
22018
Generating random Gaussian graphical models
I Córdoba, G Varando, C Bielza, P Larrañaga
arXiv preprint arXiv:1909.01062, 2019
12019
A fast Metropolis-Hastings method for generating random correlation matrices
I Córdoba, G Varando, C Bielza, P Larrañaga
International Conference on Intelligent Data Engineering and Automated …, 2018
12018
A partial orthogonalization method for simulating covariance and concentration graph matrices
I Córdoba, G Varando, C Bielza, P Larrañaga
arXiv preprint arXiv:1807.03090, 2018
12018
Learning DAGs without imposing acyclicity
G Varando
arXiv preprint arXiv:2006.03005, 2020
2020
Sparse Cholesky covariance parametrization for recovering latent structure in ordered data
I Córdoba, C Bielza, P Larrañaga, G Varando
arXiv preprint arXiv:2006.01448, 2020
2020
The R Package stagedtrees for Structural Learning of Stratified Staged Trees
F Carli, M Leonelli, E Riccomagno, G Varando
arXiv preprint arXiv:2004.06459, 2020
2020
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values
S Weichwald, ME Jakobsen, PB Mogensen, L Petersen, N Thams, ...
https://arxiv.org/abs/2002.09573, 2020
2020
Markov Property in Generative Classifiers
G Varando, C Bielza, P Larrañaga, E Riccomagno
arXiv preprint arXiv:1811.04759, 2018
2018
Theoretical studies on bayesian network classifiers
G Varando
ETS de Ingenieros Informáticos (UPM), 2018
2018
Algebraic views on classification problems
G Varando, E Riccomagno
Abstracts of the Ninth Workshop on Simulation 1, 2, 2018
2018
ALGEBRAIC REPRESENTATION OF GENERATIVE CLASSIFIER
G VARANDO, EVA RICCOMAGNO
Regression models with MoPs Bayesian networks
G Varando, C Bielza, P Larranaga
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–19