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2020 – today
- 2024
[j5]Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta:
Image Reconstruction via Deep Image Prior Subspaces. Trans. Mach. Learn. Res. 2024 (2024)- [c2]Pascal Fernsel, Zeljko Kereta, Alexander Denker:
Convergence Properties of Score-Based Models for Linear Inverse Problems Using Graduated Optimisation. MLSP 2024: 1-6 - [i16]Pascal Fernsel, Zeljko Kereta, Alexander Denker:
Convergence Properties of Score-Based Models using Graduated Optimisation for Linear Inverse Problems. CoRR abs/2404.18699 (2024) - [i15]Matthias J. Ehrhardt, Zeljko Kereta, Jingwei Liang, Junqi Tang:
A Guide to Stochastic Optimisation for Large-Scale Inverse Problems. CoRR abs/2406.06342 (2024) - [i14]Evangelos Papoutsellis, Casper O. da Costa-Luis, Daniel Deidda, Claire Delplancke, Margaret Duff, Gemma Fardell, Ashley Gillman, Jakob S. Jørgensen, Zeljko Kereta, Evgueni Ovtchinnikov, Edoardo Pasca, Georg Schramm, Kris Thielemans:
Stochastic Optimisation Framework using the Core Imaging Library and Synergistic Image Reconstruction Framework for PET Reconstruction. CoRR abs/2406.15159 (2024) - [i13]Alexander Denker, Zeljko Kereta, Imraj RD Singh, Tom Freudenberg, Tobias Kluth, Peter Maass, Simon R. Arridge:
Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data. CoRR abs/2407.01559 (2024) - [i12]Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros:
Why do we regularise in every iteration for imaging inverse problems? CoRR abs/2411.00688 (2024) - 2023
- [j4]Bangti Jin, Zeljko Kereta
:
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces. SIAM J. Imaging Sci. 16(2): 671-705 (2023) - [j3]Robert Twyman, Simon R. Arridge, Zeljko Kereta, Bangti Jin, Ludovica Brusaferri, Sangtae Ahn, Charles W. Stearns, Brian F. Hutton, Irene A. Burger, Fotis Kotasidis, Kris Thielemans:
An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction. IEEE Trans. Medical Imaging 42(1): 29-41 (2023) - [c1]Marta Lazzaretti, Zeljko Kereta, Claudio Estatico, Luca Calatroni:
Stochastic Gradient Descent for Linear Inverse Problems in Variable Exponent Lebesgue Spaces. SSVM 2023: 457-470 - [i11]Zeljko Kereta, Bangti Jin:
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces. CoRR abs/2302.05197 (2023) - [i10]Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin:
Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. CoRR abs/2302.10279 (2023) - [i9]Marta Lazzaretti, Zeljko Kereta, Luca Calatroni, Claudio Estatico:
Stochastic gradient descent for linear inverse problems in variable exponent Lebesgue spaces. CoRR abs/2303.09182 (2023) - [i8]Imraj RD Singh, Alexander Denker, Riccardo Barbano, Zeljko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon R. Arridge:
Score-Based Generative Models for PET Image Reconstruction. CoRR abs/2308.14190 (2023) - 2022
- [j2]Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger:
StreaMRAK a streaming multi-resolution adaptive kernel algorithm. Appl. Math. Comput. 426: 127112 (2022) - 2021
- [i7]Zeljko Kereta, Robert Twyman, Simon R. Arridge, Kris Thielemans, Bangti Jin:
Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions. CoRR abs/2106.03172 (2021) - [i6]Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin:
Unsupervised Knowledge-Transfer for Learned Image Reconstruction. CoRR abs/2107.02572 (2021) - [i5]Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger:
SreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm. CoRR abs/2108.10411 (2021) - 2020
- [i4]Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin:
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. CoRR abs/2011.08413 (2020)
2010 – 2019
- 2019
- [i3]Zeljko Kereta, Timo Klock, Valeriya Naumova:
Nonlinear generalization of the single index model. CoRR abs/1902.09024 (2019) - [i2]Zeljko Kereta, Johannes Maly, Valeriya Naumova:
Linear convergence and support recovery for non-convex multi-penalty regularization. CoRR abs/1908.02503 (2019) - 2018
- [i1]Ernesto De Vito, Zeljko Kereta, Valeria Naumova:
A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net. CoRR abs/1809.08696 (2018) - 2016
- [j1]Philipp Grohs, Zeljko Kereta, Uwe Wiesmann:
A shearlet-based fast thresholded Landweber algorithm for deconvolution. Int. J. Wavelets Multiresolution Inf. Process. 14(5): 1650032:1-1650032:19 (2016)
Coauthor Index
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