62 citations · 124 across the 14 of their papers we have counts for
Showing 2026 · math.OCShow all
2 papers · 2 filters
math.OC2026
A Modular Approach to Stochastic Optimisation for Inverse Problems Using the Core Imaging Library
Evangelos Papoutsellis, Margaret A. G. Duff, Jakob S. Jørgensen +5
The Core Imaging Library (CIL) is an open-source versatile Python framework for solving inverse problems with special emphasis on imaging applications such as computed tomography (…
math.OC2026
Split, Skip and Play: Variance-Reduced ProxSkip for Tomography Reconstruction is Extremely Fast
Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros
Many modern iterative solvers for large-scale tomographic reconstruction incur two major computational costs per iteration: expensive forward/adjoint projections to update the data…