Andres R. Masegosa 个人学术档案

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	总计	2019 年至今
引用	1264	763
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i10 指数	34	25

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Serafín MoralDept. Computer Science and Artificial Intelligence, University of Granada在 decsai.ugr.es 的电子邮件经过验证
Antonio SalmerónUniversity of Almería, Spain在 ual.es 的电子邮件经过验证
Helge LangsethNorwegian University of Science and Technology在 ntnu.no 的电子邮件经过验证
Thomas Dyhre NielsenAalborg University在 cs.aau.dk 的电子邮件经过验证
Joaquín AbellánProfesor del departamento de Ciencias de la Computación e Inteligencia Artificial (UGR)在 decsai.ugr.es 的电子邮件经过验证
Anders L MadsenCEO at HUGIN EXPERT and Adjunct professor at Aalborg University在 hugin.com 的电子邮件经过验证
Ana M. MartínezJoint Research Center, European Commission在 ec.europa.eu 的电子邮件经过验证
Darío Ramos-LópezProfessor of Applied Mathematics, Department of Mathematics, University of Almería, Almería (Spain)在 ual.es 的电子邮件经过验证
Andrés CanoDepartment of Computer Science and Artificial Intelligence, University of Granada在 decsai.ugr.es 的电子邮件经过验证
Rafael CabañasUniversity of Almería在 ual.es 的电子邮件经过验证
Hanen BorchaniSimCorp A/S在 simcorp.com 的电子邮件经过验证
Manuel Gómez-Olmedo (mgomez at d...Department of Computer Science and Artificial Intelligence, Universidad de Granada在 decsai.ugr.es 的电子邮件经过验证
Antonio FernándezSenior Data Scientist in Banking (Cajamar)在 bcc.es 的电子邮件经过验证
Luis A. OrtegaAutonomous University of Madrid在 uam.es 的电子邮件经过验证
Christian IgelDepartment of Computer Science, University of Copenhagen在 diku.dk 的电子邮件经过验证
Stephan Sloth Lorenzenph.d. student, Department of Computer Science, University of Copenhagen在 di.ku.dk 的电子邮件经过验证
Yevgeny SeldinProfessor, Department of Computer Science, University of Copenhagen在 di.ku.dk 的电子邮件经过验证
Rafael RumíProfessor, University of Almería在 ual.es 的电子邮件经过验证
Javier García CastellanoDepartment of Computer Science and Artificial Intelligence at University of Granada在 decsai.ugr.es 的电子邮件经过验证
Frank CoolenProfessor of Statistics, Durham University在 durham.ac.uk 的电子邮件经过验证

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Andres R. Masegosa

University of Aalborg

在 cs.aau.dk 的电子邮件经过验证 - 首页

Machine Learning Probabilistic Programming Bayesian Deep Learning Variational Inference


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Requirements for total uncertainty measures in Dempster–Shafer theory of evidence J Abellán, A Masegosa International journal of general systems 37 (6), 733-747, 2008	95	2008
A method for integrating expert knowledge when learning Bayesian networks from data A Cano, AR Masegosa, S Moral IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41 …, 2011	84	2011
Learning under Model Misspecification: Applications to Variational and Ensemble methods A Masegosa Advances in Neural Information Processing Systems 33, 2020	83	2020
An interactive approach for Bayesian network learning using domain/expert knowledge AR Masegosa, S Moral International Journal of Approximate Reasoning 54 (8), 1168-1181, 2013	80	2013
Bagging schemes on the presence of class noise in classification J Abellán, AR Masegosa Expert Systems with Applications 39 (8), 6827-6837, 2012	73	2012
Bagging decision trees on data sets with classification noise J Abellán, AR Masegosa Foundations of Information and Knowledge Systems: 6th International …, 2010	73	2010
An ensemble method using credal decision trees J Abellan, AR Masegosa European journal of operational research 205 (1), 218-226, 2010	61	2010
Second order PAC-Bayesian bounds for the weighted majority vote A Masegosa, S Lorenzen, C Igel, Y Seldin Advances in Neural Information Processing Systems 33, 2020	42	2020
Classification with decision trees from a nonparametric predictive inference perspective J Abellán, RM Baker, F Coolen, RJ Crossman, AR Masegosa Computational Statistics & Data Analysis 71, 789-802, 2014	37	2014
An experimental study about simple decision trees for bagging ensemble on datasets with classification noise J Abellán, AR Masegosa Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 10th …, 2009	34	2009
Learning from incomplete data in Bayesian networks with qualitative influences AR Masegosa, AJ Feelders, LC van der Gaag International Journal of Approximate Reasoning 69, 18-34, 2016	33	2016
Diversity and Generalization in Neural Network Ensembles LA Ortega, R Cabañas, A Masegosa International Conference on Artificial Intelligence and Statistics, 11720-11743, 2022	31	2022
Modeling concept drift: A probabilistic graphical model based approach H Borchani, AM Martínez, AR Masegosa, H Langseth, TD Nielsen, ... International Symposium on Intelligent Data Analysis, 72-83, 2015	31	2015
New skeleton-based approaches for Bayesian structure learning of Bayesian networks AR Masegosa, S Moral Applied Soft Computing 13 (2), 1110-1120, 2013	29	2013
Bayesian models of data streams with hierarchical power priors A Masegosa, TD Nielsen, H Langseth, D Ramos-López, A Salmerón, ... Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017	26	2017
Imprecise classification with credal decision trees J Abellan, AR Masegosa International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2012	26	2012
AMIDST: A Java toolbox for scalable probabilistic machine learning AR Masegosa, AM Martínez, D Ramos-López, R Cabañas, A Salmerón, ... Knowledge-Based Systems 163, 595-597, 2019	22	2019
From anecdote to evidence: the relationship between personality and need for cognition of developers D Russo, AR Masegosa, KJ Stol Empirical Software Engineering 27 (3), 1-29, 2022	19	2022
Probabilistic Graphical Models on Multi-Core CPUs Using Java 8 AR Masegosa, AM Martinez, H Borchani IEEE Computational Intelligence Magazine 11 (2), 41-54, 2016	18	2016
Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks AR Masegosa, S Moral International Journal of Approximate Reasoning 55 (7), 1548-1569, 2014	18	2014

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