Implementation of an Optimal First-Order Method for Strongly Convex Total Variation Regularization - Tobias Lindstrøm Jensen; Jakob Heide Jørgensen; Per Christian Hansen; Søren Holdt Jensen (CoRR, 2011)

Accelerated gradient methods for total-variation-based CT image reconstruction - Jakob Heide Jørgensen; Tobias Lindstrøm Jensen; Per Christian Hansen; Søren Holdt Jensen; Emil Y. Sidky; Xiaochuan Pan (CoRR, 2011)

Ensuring convergence in total-variation-based reconstruction for accurate microcalcification imaging in breast X-ray CT - Jakob Heide Jørgensen; Emil Y. Sidky; Xiaochuan Pan (CoRR, 2011)

Quantifying Admissible Undersampling for Sparsity-Exploiting Iterative Image Reconstruction in X-Ray CT. - Jakob Sauer Jørgensen; Emil Y. Sidky; Xiaochuan Pan (IEEE Trans. Medical Imaging, 2013)

Testable uniqueness conditions for empirical assessment of undersampling levels in total variation-regularized x-ray CT. - Jakob Sauer Jørgensen; Christian Kruschel; Dirk A. Lorenz (CoRR, 2014)

How little data is enough? Phase-diagram analysis of sparsity-regularized X-ray CT. - Jakob Sauer Jørgensen; Emil Y. Sidky (CoRR, 2014)

Comparison of Reconstruction Methods for Free-Space Propagation Phase-Contrast Tomography. - Rasmus Dalgas Rasmussen; Jakob Sauer Jørgensen; Henning Friis Poulsen; Per Christian Hansen (CoRR, 2015)

AIR Tools II: algebraic iterative reconstruction methods, improved implementation. - Per Christian Hansen; Jakob Sauer Jørgensen (Numer. Algorithms, 2018)

Analyzing Reconstruction Artifacts from Arbitrary Incomplete X-ray CT Data. - Leise Borg; Jürgen Frikel; Jakob Sauer Jørgensen; Eric Todd Quinto (SIAM J. Imaging Sci., 2018)

SIRF: Synergistic Image Reconstruction Framework. - Evgueni Ovtchinnikov; Richard Brown 004; Christoph Kolbitsch; Edoardo Pasca; Casper O. da Costa-Luis; Ashley Gillman; Benjamin A. Thomas; Nikos Efthimiou; Johannes Mayer; Palak Wadhwa; Matthias J. Ehrhardt; Sam Ellis; et al. (Comput. Phys. Commun., 2020)

Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography. - Per Christian Hansen; Jakob Sauer Jørgensen; Peter Winkel Rasmussen (ICCSA (Workshops), 2021)

Core Imaging Library - Part I: a versatile Python framework for tomographic imaging. - Jakob Sauer Jørgensen; Evelina Ametova; Genoveva Burca; Gemma Fardell; Evangelos Papoutsellis; Edoardo Pasca; Kris Thielemans; Martin J. Turner; Ryan Warr; William R. B. Lionheart; Philip J. Withers (CoRR, 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)

Structural Gaussian Priors for Bayesian CT reconstruction of Subsea Pipes. - Silja L. Christensen; Nicolai André Brogaard Riis; Felipe Uribe; Jakob Sauer Jørgensen (CoRR, 2022)

A Bayesian Approach to CT Reconstruction with Uncertain Geometry. - Frederik H. Pedersen; Jakob Sauer Jørgensen; Martin S. Andersen 001 (CoRR, 2022)

Low-rank flat-field correction for artifact reduction in spectral computed tomography. - Katrine O. Bangsgaard; Genoveva Burca; Evelina Ametova; Martin S. Andersen 001; Jakob Sauer Jørgensen (CoRR, 2022)

Regularized Material Decomposition for K-edge Separation in Hyperspectral Computed Tomography. - Francesca Bevilacqua; Yiqiu Dong; Jakob Sauer Jørgensen (SSVM, 2023)

CUQIpy - Part I: computational uncertainty quantification for inverse problems in Python. - Nicolai André Brogaard Riis; Amal Mohammed A. Alghamdi; Felipe Uribe; Silja L. Christensen; Babak Maboudi Afkham; Per Christian Hansen; Jakob Sauer Jørgensen (CoRR, 2023)

CUQIpy - Part II: computational uncertainty quantification for PDE-based inverse problems in Python. - Amal Mohammed A. Alghamdi; Nicolai André Brogaard Riis; Babak Maboudi Afkham; Felipe Uribe; Silja L. Christensen; Per Christian Hansen; Jakob Sauer Jørgensen (CoRR, 2023)

A directional regularization method for the limited-angle Helsinki Tomography Challenge using the Core Imaging Library (CIL). - Jakob Sauer Jørgensen; Evangelos Papoutsellis; Laura Murgatroyd; Gemma Fardell; Edoardo Pasca (CoRR, 2023)

Democratizing Uncertainty Quantification. - Linus Seelinger; Anne Reinarz; Mikkel Bue Lykkegaard; Amal Mohammed A. Alghamdi; David Aristoff; Wolfgang Bangerth; Jean Bénézech; Matteo Diez; Kurt Frey; John D. Jakeman; Jakob Sauer Jørgensen; Ki-Tae Kim; et al. (CoRR, 2024)

Adversarially Informed Neural Fields for Computed Tomography Reconstruction. - Rasmus Juul Pedersen; Luke Besley; Jakob Sauer Jørgensen; Jens Wenzel Andreasen; Anders Bjorholm Dahl; Vedrana Andersen Dahl (SCIA (1), 2025)

Democratizing uncertainty quantification. - Linus Seelinger; Anne Reinarz; Mikkel Bue Lykkegaard; Robert Akers; Amal Mohammed A. Alghamdi; David Aristoff; Wolfgang Bangerth; Jean Bénézech; Matteo Diez; Kurt Frey; John D. Jakeman; Jakob Sauer Jørgensen; et al. (J. Comput. Phys., 2025)

Fast Gaussian Processes under Monotonicity Constraints. - Chao Zhang; Jasper M. Everink; Jakob Sauer Jørgensen (CoRR, 2025)