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Gherardo Varando
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2020 – today
- 2024
- [j12]Manuele Leonelli, Gherardo Varando:
Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear. Appl. Intell. 54(2): 1734-1750 (2024) - [j11]Gherardo Varando
, Salvador Catsis, Emiliano Diaz
Pairwise causal discovery with support measure machines. Appl. Soft Comput. 150: 111030 (2024) - [j10]Manuele Leonelli, Gherardo Varando:
Structural learning of simple staged trees. Data Min. Knowl. Discov. 38(3): 1520-1544 (2024) - [i18]Kai-Hendrik Cohrs, Gherardo Varando, Nuno Carvalhais, Markus Reichstein, Gustau Camps-Valls:
Double machine learning for causal hybrid modeling - applications in the Earth sciences. CoRR abs/2402.13332 (2024) - [i17]Homer Durand, Gherardo Varando, Nathan Mankovich, Gustau Camps-Valls:
Improving generalisation via anchor multivariate analysis. CoRR abs/2403.01865 (2024) - [i16]Nathan Mankovich, Homer Durand, Emiliano Diaz, Gherardo Varando, Gustau Camps-Valls:
Recovering Latent Confounders from High-dimensional Proxy Variables. CoRR abs/2403.14228 (2024) - [i15]Manuele Leonelli, Gherardo Varando:
Context-Specific Refinements of Bayesian Network Classifiers. CoRR abs/2405.18298 (2024) - [i14]Jack Storror Carter, Manuele Leonelli, Eva Riccomagno, Gherardo Varando:
Learning Staged Trees from Incomplete Data. CoRR abs/2405.18306 (2024) - [i13]Kai-Hendrik Cohrs, Gherardo Varando, Emiliano Diaz, Vasileios Sitokonstantinou, Gustau Camps-Valls:
Large Language Models for Constrained-Based Causal Discovery. CoRR abs/2406.07378 (2024) - 2023
- [j9]Federico Carli, Manuele Leonelli, Gherardo Varando
A new class of generative classifiers based on staged tree models. Knowl. Based Syst. 268: 110488 (2023) - [j8]Emiliano Diaz
Learning latent functions for causal discovery. Mach. Learn. Sci. Technol. 4(3): 35004 (2023) - [c7]Manuele Leonelli, Gherardo Varando:
Context-Specific Causal Discovery for Categorical Data Using Staged Trees. AISTATS 2023: 8871-8888 - [i12]Manuele Leonelli, Gherardo Varando:
Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear. CoRR abs/2301.00629 (2023) - [i11]Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge:
Discovering Causal Relations and Equations from Data. CoRR abs/2305.13341 (2023) - 2022
- [j7]Federico Carli, Manuele Leonelli
The R Package stagedtrees for Structural Learning of Stratified Staged Trees. J. Stat. Softw. 102(6) (2022) - [c6]Manuele Leonelli, Gherardo Varando:
Highly Efficient Structural Learning of Sparse Staged Trees. PGM 2022: 193-204 - [i10]Manuele Leonelli, Gherardo Varando:
Structural Learning of Simple Staged Trees. CoRR abs/2203.04390 (2022) - [i9]Manuele Leonelli, Gherardo Varando:
Highly Efficient Structural Learning of Sparse Staged Trees. CoRR abs/2206.06970 (2022) - 2021
- [i8]Manuele Leonelli, Gherardo Varando:
Context-Specific Causal Discovery for Categorical Data Using Staged Trees. CoRR abs/2106.04416 (2021) - [i7]Gherardo Varando, Federico Carli, Manuele Leonelli:
Staged trees and asymmetry-labeled DAGs. CoRR abs/2108.01994 (2021) - 2020
- [j6]Irene Córdoba
Sparse Cholesky Covariance Parametrization for Recovering Latent Structure in Ordered Data. IEEE Access 8: 154614-154624 (2020) - [j5]Irene Córdoba
On generating random Gaussian graphical models. Int. J. Approx. Reason. 125: 240-250 (2020) - [c5]Gherardo Varando, Niels Richard Hansen:
Graphical continuous Lyapunov models. UAI 2020: 989-998 - [i6]Sebastian Weichwald
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values. CoRR abs/2002.09573 (2020) - [i5]Gherardo Varando, Niels Richard Hansen:
Graphical continuous Lyapunov models. CoRR abs/2005.10483 (2020) - [i4]Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando:
Sparse Cholesky covariance parametrization for recovering latent structure in ordered data. CoRR abs/2006.01448 (2020) - [i3]Gherardo Varando:
Learning DAGs without imposing acyclicity. CoRR abs/2006.03005 (2020) - [i2]Federico Carli, Manuele Leonelli, Gherardo Varando:
A new class of generative classifiers based on staged tree models. CoRR abs/2012.13798 (2020)
2010 – 2019
- 2019
- [c4]Sebastian Weichwald, Martin Emil Jakobsen, Phillip B. Mogensen, Lasse Petersen, Nikolaj Thams, Gherardo Varando:
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values. NeurIPS (Competition and Demos) 2019: 27-36 - 2018
- [b1]Gherardo Varando:
Theoretical studies on Bayesian network classifiers. Technical University of Madrid, Spain, 2018 - [c3]Irene Córdoba
A Fast Metropolis-Hastings Method for Generating Random Correlation Matrices. IDEAL (1) 2018: 117-124 - [c2]Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A partial orthogonalization method for simulating covariance and concentration graph matrices. PGM 2018: 61-72 - [i1]Gherardo Varando, Concha Bielza, Pedro Larrañaga, Eva Riccomagno:
Markov Property in Generative Classifiers. CoRR abs/1811.04759 (2018) - 2016
- [j4]Gherardo Varando
Decision functions for chain classifiers based on Bayesian networks for multi-label classification. Int. J. Approx. Reason. 68: 164-178 (2016) - 2015
- [j3]Gherardo Varando
Conditional Density Approximations with Mixtures of Polynomials. Int. J. Intell. Syst. 30(3): 236-264 (2015) - [j2]Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Decision boundary for discrete Bayesian network classifiers. J. Mach. Learn. Res. 16: 2725-2749 (2015) - [j1]Hanen Borchani
A survey on multi-output regression. WIREs Data Mining Knowl. Discov. 5(5): 216-233 (2015) - 2014
- [c1]Gherardo Varando, Concha Bielza
Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-label Classification. Probabilistic Graphical Models 2014: 519-534
Coauthor Index
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last updated on 2024-08-05 20:24 CEST by the dblp team
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