Valeria Vitelli
Valeria Vitelli
Associate Professor, Department of Biostatistics, University of Oslo, Norway
Verified email at - Homepage
Cited by
Cited by
K-mean alignment for curve clustering
LM Sangalli, P Secchi, S Vantini, V Vitelli
Computational Statistics & Data Analysis 54 (5), 1219-1233, 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 …, 2013
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
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
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
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
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
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
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
Probabilistic preference learning with the Mallows rank model
V Vitelli, Ø Sørensen, M Crispino, A Frigessi Di Rattalma, E Arjas
Journal of Machine Learning Research 18 (158), 1-49, 2018
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
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
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
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
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
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
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
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
Sparse clustering of functional data
D Floriello, V Vitelli
Journal of Multivariate Analysis 154, 1-18, 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
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