Zeljko Kereta

According to our database, Zeljko Kereta authored at least 22 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Image Reconstruction via Deep Image Prior Subspaces.

Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta

Trans. Mach. Learn. Res., 2024

Plug-and-Play Half-Quadratic Splitting for Ptychography.

Alexander Denker, Johannes Hertrich, Zeljko Kereta, Silvia Cipiccia, Ecem Erin, Simon R. Arridge

CoRR, 2024

Why do we regularise in every iteration for imaging inverse problems?

Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros

CoRR, 2024

Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data.

Alexander Denker, Zeljko Kereta, Imraj RD Singh, Tom Freudenberg, Tobias Kluth, Peter Maass, Simon R. Arridge

CoRR, 2024

Stochastic Optimisation Framework using the Core Imaging Library and Synergistic Image Reconstruction Framework for PET Reconstruction.

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

CoRR, 2024

A Guide to Stochastic Optimisation for Large-Scale Inverse Problems.

Matthias J. Ehrhardt, Zeljko Kereta, Jingwei Liang, Junqi Tang

CoRR, 2024

Convergence Properties of Score-Based Models using Graduated Optimisation for Linear Inverse Problems.

Pascal Fernsel, Zeljko Kereta, Alexander Denker

CoRR, 2024

Convergence Properties of Score-Based Models for Linear Inverse Problems Using Graduated Optimisation.

Pascal Fernsel, Zeljko Kereta, Alexander Denker

Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

2023

On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces.

Bangti Jin, Zeljko Kereta

SIAM J. Imaging Sci., June, 2023

An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction.

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

IEEE Trans. Medical Imaging, 2023

Score-Based Generative Models for PET Image Reconstruction.

Imraj RD Singh, Alexander Denker, Riccardo Barbano, Zeljko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon R. Arridge

CoRR, 2023

Fast and Painless Image Reconstruction in Deep Image Prior Subspaces.

Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin

CoRR, 2023

Stochastic Gradient Descent for Linear Inverse Problems in Variable Exponent Lebesgue Spaces.

Marta Lazzaretti, Zeljko Kereta, Claudio Estatico, Luca Calatroni

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

2022

StreaMRAK a streaming multi-resolution adaptive kernel algorithm.

Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger

Appl. Math. Comput., 2022

2021

SreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm.

Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger

CoRR, 2021

Unsupervised Knowledge-Transfer for Learned Image Reconstruction.

Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin

CoRR, 2021

Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions.

Zeljko Kereta, Robert Twyman, Simon R. Arridge, Kris Thielemans, Bangti Jin

CoRR, 2021

2020

Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction.

Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin

CoRR, 2020

2019

Linear convergence and support recovery for non-convex multi-penalty regularization.

Zeljko Kereta, Johannes Maly, Valeriya Naumova

CoRR, 2019

Nonlinear generalization of the single index model.

Zeljko Kereta, Timo Klock, Valeriya Naumova

CoRR, 2019

2018

A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net.

Ernesto De Vito, Zeljko Kereta, Valeria Naumova

CoRR, 2018

2016

A shearlet-based fast thresholded Landweber algorithm for deconvolution.

Philipp Grohs, Zeljko Kereta, Uwe Wiesmann

Int. J. Wavelets Multiresolution Inf. Process., 2016