Martin Tveten
Martin Tveten
Research Scientist, Norwegian Computing Center
Verified email at nr.no
Title
Cited by
Cited by
Year
Which principal components are most sensitive in the change detection problem?
M Tveten
Stat 8 (1), e252, 2019
5*2019
kdensity: Kernel Density Estimation with Parametric Starts and Asymmetric Kernels
J Moss, M Tveten
R package version 1 (0), 2018
52018
kdensity: an R package for kernel density estimation with parametric starts and asymmetric kernels
J Moss, M Tveten
Journal of Open Source Software 4 (42), 1566, 2019
32019
Scalable changepoint and anomaly detection in cross-correlated data with an application to condition monitoring
M Tveten, IA Eckley, P Fearnhead
arXiv preprint arXiv:2010.06937, 2020
22020
Online detection of sparse changes in high-dimensional data streams using tailored projections
M Tveten, IK Glad
arXiv preprint arXiv:1908.02029, 2019
22019
Multi-Stream Sequential Change Detection--Using Sparsity and Dimension Reduction
M Tveten
22017
Real-time prediction of propulsion motor overheating using machine learning
KH Hellton, M Tveten, M Stakkeland, S Engebretsen, O Haug, M Aldrin
Journal of Marine Engineering & Technology, 1-9, 2021
2021
Scalable change and anomaly detection in cross-correlated data
M Tveten
2021
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Articles 1–8