https://orcid.org/0000-0002-6339-652X
Research Interests
Inverse Problems, Variational Methods, Imaging, Data science
Teaching
I am teaching Inverse Problems together with Hanne Kekkonen in Michaelmas term 2019/2020.
I taught Inverse Problems in Imaging in Michaelmas term 2018/2019.
Personal Web Page
NB: the list of publications below is generated automatically and incomplete. For an up-to-date list and more details about my research please visit my personal web page yury-korolev.gitlab.io.
Publications
Variational regularisation for inverse problems with imperfect forward operators and general noise models.
– CoRR
(2020)
abs/2005.14131,
Convergence rates and structure of solutions of inverse problems with imperfect forward models
– Inverse Problems
(2019)
35,
024006
(DOI: 10.1088/1361-6420/aaf6f5)
Total Variation Regularisation with Spatially Variable Lipschitz Constraints.
– CoRR
(2019)
abs/1912.02768,
HPC Implementation of the Multipoint Approximation Method for Large Scale Design Optimization Problems Under Uncertainty
(2019)
296
(DOI: 10.1007/978-3-319-97773-7_27)
A Total Variation Based Regularizer Promoting Piecewise-Lipschitz Reconstructions
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
(2019)
11603,
485
(DOI: 10.1007/978-3-030-22368-7_38)
Image reconstruction with imperfect forward models and applications in deblurring
– SIAM Journal on Imaging Sciences
(2018)
11,
197
(DOI: 10.1137/17m1141965)
Design Optimization Under Uncertainty Using the Multipoint Approximation Method
– 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017
(2017)
(DOI: 10.2514/6.2017-1934)
Diffusion Tensor Imaging with Deterministic Error Bounds
– Journal of Mathematical Imaging and Vision
(2016)
56,
137
(DOI: 10.1007/s10851-016-0639-7)
Automatic optimizer vs human optimizer for low-order jet noise modelling
– 21st AIAA/CEAS Aeroacoustics Conference
(2016)
(DOI: 10.2514/6.2015-2215)
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