Valeria Vitelli 个人学术档案

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引用	1921	1301
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Simone VantiniAssociate Professor of Statistics, MOX - Department of Mathematics, Politecnico di Milano在 polimi.it 的电子邮件经过验证
Piercesare SecchiProfessor of Statistics在 polimi.it 的电子邮件经过验证
Enrico ZioProfessor Mines Paris/PSL and Politecnico di. Milano在 mines-paristech.fr 的电子邮件经过验证
Ronay AkNational Institute of Standards and Technology在 nist.gov 的电子邮件经过验证
Arnoldo FrigessiUniversity of Oslo在 medisin.uio.no 的电子邮件经过验证
Laura Maria SangalliMOX - Dipartimento di Matematica, Politecnico di Milano在 polimi.it 的电子邮件经过验证
Jie LiuAssociate Professor, Beihang University在 buaa.edu.cn 的电子邮件经过验证
Francesca IevaAssociate Professor, MOX - Department of Mathematics, Politecnico di Milano在 polimi.it 的电子邮件经过验证
Anna Maria PaganoniProfessore di Statistica, Politecnico di Milano, Italy在 polimi.it 的电子邮件经过验证
Marta CrispinoBank of Italy在 bocconialumni.it 的电子邮件经过验证
Elja ArjasEmeritus Professor of Biometry, University of Helsinki在 helsinki.fi 的电子邮件经过验证
Yan-Fu LiProfessor, Tsinghua University, China在 tsinghua.edu.cn 的电子邮件经过验证
Øystein SørensenProfessor of Biostatistics, Department of Psychology, University of Oslo在 psykologi.uio.no 的电子邮件经过验证
Davide PigoliDepartment of Mathematics, King's College London在 kcl.ac.uk 的电子邮件经过验证
Mazyar Yazdani, Ph.D.Senior Scientist at Oslo University Hospital – Rikshospitalet, Oslo, Norway在 ous-hf.no 的电子邮件经过验证
Janicke L. JensenProfessor i oral kirurgi og oral medisin ved Det odontologiske fakultet, UiO在 odont.uio.no 的电子邮件经过验证
Christian PageNorwegian Institute of Public Health在 fhi.no 的电子邮件经过验证
Eric Westman, ProfessorDivision of Clinical Geriatrics, NVS, Karolinska Institutet在 ki.se 的电子邮件经过验证
Andrew SimmonsKing's College London, Institute of Psychiatry在 kcl.ac.uk 的电子邮件经过验证
Per Kristian Eide MD PhDProfessor of Neurosurgery, Oslo University Hospital-Rikshospitalet. University of Oslo, Oslo, Norway在 medisin.uio.no 的电子邮件经过验证

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Valeria Vitelli

Associate Professor, Department of Biostatistics, University of Oslo, Norway

在 medisin.uio.no 的电子邮件经过验证 - 首页

preference learning functional data analysis clustering high-dimensional data Bayesian methods


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
K-mean alignment for curve clustering LM Sangalli, P Secchi, S Vantini, V Vitelli Computational Statistics & Data Analysis 54 (5), 1219-1233, 2010	193	2010
Multivariate functional clustering for the morphological analysis of electrocardiograph curves F Ieva, AM Paganoni, D Pigoli, V Vitelli Journal of the Royal Statistical Society Series C: Applied Statistics 62 (3 …, 2013	139*	2013
The Evans’ Index revisited: new cut-off levels for use in radiological assessment of ventricular enlargement in the elderly MK Brix, E Westman, A Simmons, GA Ringstad, PK Eide, ... European journal of radiology 95, 28-32, 2017	135	2017
Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome MR Aure, V Vitelli, S Jernström, S Kumar, M Krohn, EU Due, TH Haukaas, ... Breast Cancer Research 19, 1-18, 2017	103	2017
Nuclear power plant components condition monitoring by probabilistic support vector machine J Liu, R Seraoui, V Vitelli, E Zio Annals of Nuclear Energy 56, 23-33, 2013	102	2013
Molecular features of subtype-specific progression from ductal carcinoma in situ to invasive breast cancer R Lesurf, MR Aure, HH Mørk, V Vitelli, T Sauer, J Geisler, S Hofvind, ... Cell reports 16 (4), 1166-1179, 2016	100	2016
An interval-valued neural network approach for uncertainty quantification in short-term wind speed prediction R Ak, V Vitelli, E Zio IEEE transactions on neural networks and learning systems 26 (11), 2787-2800, 2015	98	2015
Probabilistic preference learning with the Mallows rank model V Vitelli, Ø Sørensen, M Crispino, A Frigessi, E Arjas Journal of Machine Learning Research 18 (158), 1-49, 2018	79	2018
A novel dynamic-weighted probabilistic support vector regression-based ensemble for prognostics of time series data J Liu, V Vitelli, E Zio, R Seraoui IEEE Transactions on Reliability 64 (4), 1203-1213, 2015	79	2015
NSGA-II-trained neural network approach to the estimation of prediction intervals of scale deposition rate in oil & gas equipment R Ak, Y Li, V Vitelli, E Zio, EL Droguett, CMC Jacinto Expert Systems with Applications 40 (4), 1205-1212, 2013	78	2013
Adequacy assessment of a wind-integrated system using neural network-based interval predictions of wind power generation and load R Ak, YF Li, V Vitelli, E Zio International Journal of Electrical Power & Energy Systems 95, 213-226, 2018	58	2018
Bagging Voronoi classifiers for clustering spatial functional data P Secchi, S Vantini, V Vitelli International journal of applied earth observation and geoinformation 22, 53-64, 2013	57	2013
A cumulative genetic risk score predicts progression in P arkinson's disease L Pihlstrøm, KR Morset, E Grimstad, V Vitelli, M Toft Movement Disorders 31 (4), 487-490, 2016	53	2016
Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan P Secchi, S Vantini, V Vitelli Statistical Methods & Applications 24, 279-300, 2015	50	2015
Utility of tear osmolarity measurement in diagnosis of dry eye disease B Tashbayev, TP Utheim, ØA Utheim, S Ræder, JL Jensen, M Yazdani, ... Scientific reports 10 (1), 5542, 2020	46	2020
Functional clustering and alignment methods with applications V Vitelli, LM Sangalli, P Secchi, S Vantini Communications in Applied and Industrial Mathematics 1 (1), 205-224, 2010	43	2010
Altered neuroendocrine control and association to clinical symptoms in adolescent chronic fatigue syndrome: a cross-sectional study V Bruun Wyller, V Vitelli, D Sulheim, E Fagermoen, A Winger, K Godang, ... Journal of Translational Medicine 14 (121), 2016	41	2016
Treelet decomposition of mobile phone data for deriving city usage and mobility pattern in the Milan urban region F Manfredini, P Pucci, P Secchi, P Tagliolato, S Vantini, V Vitelli Advances in complex data modeling and computational methods in statistics …, 2015	40	2015
Sparse clustering of functional data D Floriello, V Vitelli Journal of Multivariate Analysis 154, 1-18, 2017	33	2017
A genetic algorithm and neural network technique for predicting wind power under uncertainty YFL Ronay Aka, V Vitellia, E Zio Chemical Engineering 33, 2013	29	2013

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