Zeljko Kereta

32 papers Journal 28Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
CMAD: Cooperative Multi-Agent Diffusion via Stochastic Optimal Control.
CoRR
Riccardo Barbano, Alexander Denker, Zeljko Kereta, Runchang Li, Francisco Vargas
2026 J jnl
Stochastic Gradient Descent for Nonlinear Inverse Problems in Banach Spaces.
CoRR
Bangti Jin, Zeljko Kereta, Yuxin Xia
2026 J jnl
Trajectory Stitching for Solving Inverse Problems with Flow-Based Models.
CoRR
Alexander Denker, Moshe Eliasof, Zeljko Kereta, Carola-Bibiane Schönlieb
2025 J jnl
Graph Neural Regularizers for PDE Inverse Problems.
CoRR
William Lauga, James Rowbottom, Alexander Denker, Zeljko Kereta, Moshe Eliasof, Carola-Bibiane Schönlieb
2025 J jnl
Learning Binary Sampling Patterns for Single-Pixel Imaging using Bilevel Optimisation.
CoRR
Serban Cristian Tudosie, Alexander Denker, Zeljko Kereta, Simon R. Arridge
2025 J jnl
Learning Regularization Functionals for Inverse Problems: A Comparative Study.
CoRR
Johannes Hertrich, Hok Shing Wong, Alexander Denker, Stanislas Ducotterd, Zhenghan Fang, Markus Haltmeier, Zeljko Kereta, Erich Kobler, Oscar Leong, Mohammad Sadegh Salehi, Carola-Bibiane Schönlieb, Johannes Schwab, Zakhar Shumaylov, Jeremias Sulam, German Shâma Wache, Martin Zach, Yasi Zhang, Matthias J. Ehrhardt, Sebastian Neumayer
2025 — conf
Plug-and-Play Half-Quadratic Splitting for Ptychography.
SSVM (1)
Alexander Denker, Johannes Hertrich, Zeljko Kereta, Silvia Cipiccia, Ecem Erin, Simon R. Arridge
2025 — conf
Why do we Regularise in Every Iteration for Imaging Inverse Problems?
SSVM (1)
Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros
2024 J jnl
A Guide to Stochastic Optimisation for Large-Scale Inverse Problems.
CoRR
Matthias J. Ehrhardt, Zeljko Kereta, Jingwei Liang, Junqi Tang
2024 — conf
Convergence Properties of Score-Based Models for Linear Inverse Problems Using Graduated Optimisation.
MLSP
Pascal Fernsel, Zeljko Kereta, Alexander Denker
2024 J jnl
Convergence Properties of Score-Based Models using Graduated Optimisation for Linear Inverse Problems.
CoRR
Pascal Fernsel, Zeljko Kereta, Alexander Denker
2024 J jnl
Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data.
CoRR
Alexander Denker, Zeljko Kereta, Imraj RD Singh, Tom Freudenberg, Tobias Kluth, Peter Maass, Simon R. Arridge
2024 J jnl
Image Reconstruction via Deep Image Prior Subspaces.
Trans. Mach. Learn. Res.
Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta
2024 J jnl
Plug-and-Play Half-Quadratic Splitting for Ptychography.
CoRR
Alexander Denker, Johannes Hertrich, Zeljko Kereta, Silvia Cipiccia, Ecem Erin, Simon R. Arridge
2024 J jnl
Stochastic Optimisation Framework using the Core Imaging Library and Synergistic Image Reconstruction Framework for PET Reconstruction.
CoRR
Evangelos Papoutsellis, Casper O. da Costa-Luis, Daniel Deidda, Claire Delplancke, Margaret Duff, Gemma Fardell, Ashley Gillman, Jakob Sauer Jørgensen, Zeljko Kereta, Evgueni Ovtchinnikov, Edoardo Pasca, Georg Schramm, Kris Thielemans
2024 J jnl
Why do we regularise in every iteration for imaging inverse problems?
CoRR
Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros
2023 J jnl
An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction.
IEEE Trans. Medical Imaging
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
2023 J jnl
Fast and Painless Image Reconstruction in Deep Image Prior Subspaces.
CoRR
Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin
2023 J jnl
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces.
CoRR
Zeljko Kereta, Bangti Jin
2023 J jnl
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces.
SIAM J. Imaging Sci.
Bangti Jin, Zeljko Kereta
2023 J jnl
Score-Based Generative Models for PET Image Reconstruction.
CoRR
Imraj RD Singh, Alexander Denker, Riccardo Barbano, Zeljko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon R. Arridge
2023 — conf
Stochastic Gradient Descent for Linear Inverse Problems in Variable Exponent Lebesgue Spaces.
SSVM
Marta Lazzaretti, Zeljko Kereta, Claudio Estatico, Luca Calatroni
2023 J jnl
Stochastic gradient descent for linear inverse problems in variable exponent Lebesgue spaces.
CoRR
Marta Lazzaretti, Zeljko Kereta, Luca Calatroni, Claudio Estatico
2022 J jnl
StreaMRAK a streaming multi-resolution adaptive kernel algorithm.
Appl. Math. Comput.
Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger
2021 J jnl
SreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm.
CoRR
Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger
2021 J jnl
Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions.
CoRR
Zeljko Kereta, Robert Twyman, Simon R. Arridge, Kris Thielemans, Bangti Jin
2021 J jnl
Unsupervised Knowledge-Transfer for Learned Image Reconstruction.
CoRR
Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
2020 J jnl
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction.
CoRR
Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
2019 J jnl
Linear convergence and support recovery for non-convex multi-penalty regularization.
CoRR
Zeljko Kereta, Johannes Maly, Valeriya Naumova
2019 J jnl
Nonlinear generalization of the single index model.
CoRR
Zeljko Kereta, Timo Klock, Valeriya Naumova
2018 J jnl
A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net.
CoRR
Ernesto De Vito, Zeljko Kereta, Valeria Naumova
2016 J jnl
A shearlet-based fast thresholded Landweber algorithm for deconvolution.
Int. J. Wavelets Multiresolution Inf. Process.
Philipp Grohs, Zeljko Kereta, Uwe Wiesmann