Scalable changepoint and anomaly detection in cross-correlated data with an application to condition monitoring M Tveten, IA Eckley, P Fearnhead Annals of Applied Statistics 16 (2), 721-743, 2022 | 14 | 2022 |
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 | 14 | 2019 |
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 21 (6), 334-342, 2022 | 13 | 2022 |
kdensity: Kernel Density Estimation with Parametric Starts and Asymmetric Kernels. R package version 1.0. 1 J Moss, M Tveten | 11 | 2019 |
Which principal components are most sensitive in the change detection problem? M Tveten Stat 8 (1), e252, 2019 | 10* | 2019 |
Online detection of sparse changes in high-dimensional data streams using tailored projections M Tveten, IK Glad arXiv preprint arXiv:1908.02029, 2019 | 3 | 2019 |
Multi-Stream Sequential Change Detection--Using Sparsity and Dimension Reduction M Tveten | 2 | 2017 |
Efficient sparsity adaptive changepoint estimation PAJ Moen, IK Glad, M Tveten Electronic Journal of Statistics 18 (2), 3975-4038, 2024 | 1 | 2024 |
Fault detection in propulsion motors in the presence of concept drift M Tveten, M Stakkeland arXiv preprint arXiv:2406.08030, 2024 | | 2024 |
Scalable change and anomaly detection in cross-correlated data M Tveten, IK Glad, NL Hjort Universitetet i Oslo, 2021 | | 2021 |