On the Convergence of the Stochastic Primal-Dual Hybrid Gradient for Convex Optimization. - Eric B. Gutiérrez; Claire Delplancke; Matthias J. Ehrhardt (CoRR, 2020)

Convergence Properties of a Randomized Primal-Dual Algorithm with Applications to Parallel MRI. - Eric B. Gutiérrez; Claire Delplancke; Matthias J. Ehrhardt (SSVM, 2021)

Core Imaging Library - Part II: Multichannel reconstruction for dynamic and spectral tomography. - Evangelos Papoutsellis; Evelina Ametova; Claire Delplancke; Gemma Fardell; Jakob Sauer Jørgensen; Edoardo Pasca; Martin J. Turner; Ryan Warr; William R. B. Lionheart; Philip J. Withers (CoRR, 2021)

On the convergence and sampling of randomized primal-dual algorithms and their application to parallel MRI reconstruction. - Eric B. Gutiérrez; Claire Delplancke; Matthias J. Ehrhardt (CoRR, 2022)

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; et al. (CoRR, 2024)

Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes. - Antonin Chambolle; Claire Delplancke; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb; Junqi Tang (J. Math. Imaging Vis., 2024)

Randomized Primal-Dual Algorithm with Arbitrary Sampling: Convergence Theory and Applications to Parallel MRI. - Eric B. Gutiérrez; Claire Delplancke; Matthias J. Ehrhardt (J. Math. Imaging Vis., 2025)