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Department of Applied Mathematics and Theoretical Physics

 

I moved to the Department of Mathematical Sciences at the University of Bath. This is my new department web page. My personal web page is yury-korolev.gitlab.io.

 

Research Interests

Inverse Problems, Variational Methods, Mathematical Imaging, Mathematics of Machine Learning

Teaching

I taught Introduction to Nonlinear Spectral Analysis in Lent term 2021/2022 and Inverse Problems in 2018/2019, 2019/2020 and 2020/2021.

Personal Web Page

NB: the list of publications below is generated automatically and may be incomplete. For an up-to-date list and more details about my research and teaching please visit my personal web page yury-korolev.gitlab.io.

 

Publications

Eigenvalue problems in 𝐿^{∞}: optimality conditions, duality, and relations with optimal transport
L Bungert, Y Korolev
– Communications of the American Mathematical Society
(2022)
2,
345
Gaussian random fields on non-separable Banach spaces
Y Korolev, J Latz, C-B Schönlieb
(2022)
Data Driven Reconstruction Using Frames and Riesz Bases
A Aspri, L Frischauf, Y Korolev, O Scherzer
(2021)
303
Eigenvalue Problems in $\mathrm{L}^\infty$: Optimality Conditions, Duality, and Relations with Optimal Transport
L Bungert, Y Korolev
– Comm. Amer. Math. Soc. 2 (2022), 345-373
(2021)
Two-layer neural networks with values in a Banach space
Y Korolev
(2021)
Data driven regularization by projection
A Aspri, Y Korolev, O Scherzer
– Inverse Problems
(2020)
36,
125009
Variational regularisation for inverse problems with imperfect forward operators and general noise models
L Bungert, M Burger, Y Korolev, C-B Schönlieb
– Inverse Probl
(2020)
36,
125014
Structural analysis of an $L$-infinity variational problem and relations to distance functions
L Bungert, Y Korolev, M Burger
– Pure and Applied Analysis
(2020)
2,
703
Deeply learned spectral total variation decomposition
TG Grossmann, Y Korolev, G Gilboa, CB Schönlieb
– Advances in Neural Information Processing Systems
(2020)
2020-December,
Total Variation Regularisation with Spatially Variable Lipschitz Constraints.
M Burger, Y Korolev, S Parisotto, C-B Schönlieb
– CoRR
(2019)
abs/1912.02768,
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Research Group

Cambridge Image Analysis

Room

F0.14