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2022
A. M. Bruaset, G. T. Lines and J. Sundnes. "Data aggregation and anonymization for mathematical modeling and epidemiological studies." In Smittestopp - A Case Study on Digital Contact Tracing, edited by A. Elmokashfi, O. Lysne and V. Naumova, 121-141. Vol. 11. Cham: Springer International Publishing, 2022.
A. Elmokashfi, S. W. Funke, T. Klock, M. Kuchta, V. Naumova and J. J. Uv. "Digital tracing, validation, and reporting." In Smittestopp − A Case Study on Digital Contact Tracing, edited by A. Elmokashfi, O. Lysne and V. Naumova, 99-120. Vol. 11. Cham: Springer International Publishing, 2022.
A. Elmokashfi, S. W. Funke, T. Klock, M. Kuchta, V. Naumova and J. J. Uv. "Digital tracing, validation, and reporting." In Smittestopp − A Case Study on Digital Contact Tracing, edited by A. Elmokashfi, O. Lysne and V. Naumova, 99-120. Vol. 11. Cham: Springer International Publishing, 2022.
A. Elmokashfi, O. Lysne and V. Naumova. Smittestopp − A Case Study on Digital Contact Tracing In Simula SpringerBriefs on Computing. Vol. 11. Cham: Springer Nature, 2022.
2019
P. M. Florvaag, V. Naumova and K. Valen-Sendstad. Automated and objective segmentation of medical image using machine learning techniques: all models are wrong, but some are useful In Computational and Mathematical Biomedical Engineering. Sendai, Japan: CMBE, 2019.File no_pdf_yet.docx (21.56 KB)
M. Fornasier, E. De Vito, Z. Kereta and V. Naumova. Automated parameter estimation for selected inverse problems In Grenoble, France., 2019.
P. M. Florvaag, V. Strøm, C. Glinge, R. Jabbari, N. Vejlstrup, T. Engstrom, K. A. Ahtarovski, T. Jespersen, J. Tfelt-Hansen, V. Naumova et al. A Combined In-Silico and Machine Learning Approach towards Predicting Arrhythmic Risk in Post-Infarction Patients In Computing in Cardiology, Singapore., 2019.
Z. Kereta, T. Klock and V. Naumova. Covariance and precision matrix estimation, and dimension reduction in regression problems In Oslo, Norway., 2019.
Z. Kereta, V. Naumova and J. Maly. Linear convergence and support recovery for non-convex multi-penalty regularization. SPARS 2019, Toulouse, France, 2019.
E. De Vito, Z. Kereta, V. Naumova, L. Rosasco and S. Vigogna. Monte Carlo wavelets: a randomized approach to frame discretization In Sampling Theory and Applications. IEEE, 2019.
Z. Kereta, T. Klock and V. Naumova. "Nonlinear generalization of the monotone single index model." Information and Inference (2019).
Z. Kereta, T. Klock and V. Naumova. Towards nonlinear sufficient dimension reduction In AIP conference, Grenoble, France., 2019.
E. De Vito, Z. Kereta and V. Naumova. "Unsupervised parameter selection for denoising with the elastic net." Machine Learning (2019).
E. De Vito, Z. Kereta and V. Naumova. Unsupervised Parameter Selection in Variational Regularization. SPARS 2019, Toulouse, France, 2019.

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