Combinatorial Problems in High-Performance Computing: Partitioning. - Rob H. Bisseling; Tristan van Leeuwen; Ümit V. Çatalyürek (Combinatorial Scientific Computing, 2009)

Raising the order of multivariate approximation schemes using supplementary derivative data. - Dirk Kraaijpoel; Tristan van Leeuwen (ICCS, 2010)

Robust inversion via semistochastic dimensionality reduction. - Aleksandr Y. Aravkin; Michael P. Friedlander; Tristan van Leeuwen (ICASSP, 2012)

Robust inversion, dimensionality reduction, and randomized sampling. - Aleksandr Y. Aravkin; Michael P. Friedlander; Felix J. Herrmann; Tristan van Leeuwen (Math. Program., 2012)

Sparse seismic imaging using variable projection. - Aleksandr Y. Aravkin; Tristan van Leeuwen; Ning Tu (ICASSP, 2013)

Adaptive Grid Refinement for Discrete Tomography. - Tristan van Leeuwen; Kees Joost Batenburg (DGCI, 2014)

3D Frequency-Domain Seismic Inversion with Controlled Sloppiness. - Tristan van Leeuwen; Felix J. Herrmann (SIAM J. Sci. Comput., 2014)

Easy implementation of advanced tomography algorithms using the ASTRA toolbox with Spot operators. - Folkert Bleichrodt; Tristan van Leeuwen; Willem Jan Palenstijn; Wim van Aarle; Jan Sijbers; Kees Joost Batenburg (Numer. Algorithms, 2016)

A Parametric Level-Set Method for Partially Discrete Tomography. - Ajinkya Kadu; Tristan van Leeuwen; Kees Joost Batenburg (DGCI, 2017)

Joint parameter and state estimation for wave-based imaging and inversion. - Tristan van Leeuwen (ICASSP, 2017)

Geometric Imaging for Subsurface Salt Bodies. - Tristan van Leeuwen; Ajinkya Kadu; Wim A. Mulder (ERCIM News, 2017)

An adjoint-free method to determine conditional nonlinear optimal perturbations. - Aleid Oosterwijk; Henk A. Dijkstra; Tristan van Leeuwen (Comput. Geosci., 2017)

Salt Reconstruction in Full-Waveform Inversion With a Parametric Level-Set Method. - Ajinkya Kadu; Tristan van Leeuwen; Wim A. Mulder (IEEE Trans. Computational Imaging, 2017)

A Novel Tomographic Reconstruction Method Based on the Robust Student's t Function For Suppressing Data Outliers. - Daniil Kazantsev; Folkert Bleichrodt; Tristan van Leeuwen; Anders Kaestner; Philip J. Withers; Kees Joost Batenburg; Peter D. Lee (IEEE Trans. Computational Imaging, 2017)

A convex formulation for Discrete Tomography. - Ajinkya Kadu; Tristan van Leeuwen (CoRR, 2018)

Total Variation Regularization Strategies in Full-Waveform Inversion. - Ernie Esser; Lluís Guasch; Tristan van Leeuwen; Aleksandr Y. Aravkin; Felix J. Herrmann (SIAM J. Imaging Sci., 2018)

Efficient Quadratic Penalization Through the Partial Minimization Technique. - Aleksandr Y. Aravkin; Dmitriy Drusvyatskiy; Tristan van Leeuwen (IEEE Trans. Autom. Control., 2018)

Data-Driven Modeling for Wave-Propagation. - Tristan van Leeuwen; Peter Jan van Leeuwen; Sergiy Zhuk (ENUMATH, 2019)

Fast ultrasonic imaging using end-to-end deep learning. - Georgios Pilikos; Lars Horchens; Kees Joost Batenburg; Tristan van Leeuwen; Felix Lucka (CoRR, 2020)

Deep data compression for approximate ultrasonic image formation. - Georgios Pilikos; Lars Horchens; Kees Joost Batenburg; Tristan van Leeuwen; Felix Lucka (CoRR, 2020)

CoShaRP: A Convex Program for Single-shot Tomographic Shape Sensing. - Ajinkya Kadu; Tristan van Leeuwen; Kees Joost Batenburg (CoRR, 2020)

Comparing RSVD and Krylov methods for linear inverse problems. - Nick Luiken; Tristan van Leeuwen (Comput. Geosci., 2020)

Task-Driven Learned Hyperspectral Data Reduction Using End-to-End Supervised Deep Learning. - Mathé T. Zeegers; Daniël Maria Pelt; Tristan van Leeuwen; Robert van Liere; Kees Joost Batenburg (J. Imaging, 2020)

A Convex Formulation for Binary Tomography. - Ajinkya Kadu; Tristan van Leeuwen (IEEE Trans. Computational Imaging, 2020)

Deep Learning for Multi-View Ultrasonic Image Fusion. - Georgios Pilikos; Lars Horchens; Tristan van Leeuwen; Felix Lucka (CoRR, 2021)

Single Plane-Wave Imaging using Physics-Based Deep Learning. - Georgios Pilikos; Chris L. de Korte; Tristan van Leeuwen; Felix Lucka (CoRR, 2021)

WaRIance: wavefield reconstruction inversion with stochastic variable projection. - Gabrio Rizzuti; Tristan van Leeuwen (CoRR, 2021)

ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography. - Mathé T. Zeegers; Ajinkya Kadu; Tristan van Leeuwen; Kees Joost Batenburg (CoRR, 2021)

Unsupervised Foreign Object Detection Based on Dual-Energy Absorptiometry in the Food Industry. - Vladyslav Andriiashen; Robert van Liere; Tristan van Leeuwen; Kees Joost Batenburg (J. Imaging, 2021)

Variable Projection for NonSmooth Problems. - Tristan van Leeuwen; Aleksandr Y. Aravkin (SIAM J. Sci. Comput., 2021)

Relaxed Regularization for Linear Inverse Problems. - Nick Luiken; Tristan van Leeuwen (SIAM J. Sci. Comput., 2021)

A tomographic workflow to enable deep learning for X-ray based foreign object detection. - Mathé T. Zeegers; Tristan van Leeuwen; Daniël Maria Pelt; Sophia Bethany Coban; Robert van Liere; Kees Joost Batenburg (Expert Syst. Appl., 2022)

Joint Retrospective Motion Correction and Reconstruction for Brain MRI With a Reference Contrast. - Gabrio Rizzuti; Alessandro Sbrizzi; Tristan van Leeuwen (IEEE Trans. Computational Imaging, 2022)

TOP-CT: Trajectory With Overlapping Projections X-Ray Computed Tomography. - Dirk Elias Schut; Kees Joost Batenburg; Robert van Liere; Tristan van Leeuwen (IEEE Trans. Computational Imaging, 2022)

Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification. - Rafael Orozco; Mathias Louboutin; Ali Siahkoohi; Gabrio Rizzuti; Tristan van Leeuwen; Felix Johan Herrmann (MIDL, 2023)

Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification. - Rafael Orozco; Ali Siahkoohi; Gabrio Rizzuti; Tristan van Leeuwen; Felix J. Herrmann (Image Processing, 2023)

A data-driven approach to solving a 1D inverse scattering problem. - Tristan van Leeuwen; Andreas Tataris (CoRR, 2023)

Quantifying the effect of X-ray scattering for data generation in real-time defect detection. - Vladyslav Andriiashen; Robert van Liere; Tristan van Leeuwen; Kees Joost Batenburg (CoRR, 2023)

2DeteCT - A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning. - Maximilian B. Kiss; Sophia Bethany Coban; Kees Joost Batenburg; Tristan van Leeuwen; Felix Lucka (CoRR, 2023)

Inside out: Fusing 3D imaging modalities for the internal and external investigation of multi-material museum objects. - Francien G. Bossema; Paul J. C. van Laar; Kimberly Meechan; Daniel O'Flynn; Joanne Dyer; Tristan van Leeuwen; Suzan Meijer; Erma Hermens; Kees Joost Batenburg (Digit. Appl. Archaeol. Cult. Heritage, 2023)

Time-Resolved Reconstruction of Motion, Force, and Stiffness Using Spectro-Dynamic MRI. - Max H. C. van Riel; Tristan van Leeuwen; Cornelis A. T. van den Berg; Alessandro Sbrizzi (IEEE Trans. Computational Imaging, 2023)

Experimental Validation of Ultrasound Beamforming with End-to-End Deep Learning for Single Plane Wave Imaging. - Ryan A. L. Schoop; Gijs A. G. M. Hendriks; Tristan van Leeuwen; Chris L. de Korte; Felix Lucka (CoRR, 2024)

Exploring Out-of-distribution Detection for Sparse-view Computed Tomography with Diffusion Models. - Ezgi Demircan-Tureyen; Felix Lucka; Tristan van Leeuwen (CoRR, 2024)

Task-Adaptive Angle Selection for Computed Tomography-Based Defect Detection. - Tianyuan Wang; Virginia Florian; Richard Schielein; Christian Kretzer; Stefan Kasperl; Felix Lucka; Tristan van Leeuwen (J. Imaging, 2024)

Data-Driven Discovery of Mechanical Models Directly From MRI Spectral Data. - David G. J. Heesterbeek; Max H. C. van Riel; Tristan van Leeuwen; Cornelis A. T. van den Berg; Alessandro Sbrizzi (IEEE Trans. Computational Imaging, 2024)

Sequential Experimental Design for X-Ray CT Using Deep Reinforcement Learning. - Tianyuan Wang; Felix Lucka; Tristan van Leeuwen (IEEE Trans. Computational Imaging, 2024)

Bi-level Optimization and Implicit Differentiation as a Framework for Optimal Experimental Design in Tomography. - Hamid Fathi; Alexander Skorikov; Tristan van Leeuwen (SSVM (2), 2025)

AC-IND: Sparse CT Reconstruction Based on Attenuation Coefficient Estimation and Implicit Neural Distribution. - Wangduo Xie; Richard Schoonhoven; Tristan van Leeuwen; Matthew B. Blaschko (WACV, 2025)

PtyGenography: using generative models for regularization of the phase retrieval problem. - Selin Aslan; Tristan van Leeuwen; Allard P. Mosk; Palina Salanevich (CoRR, 2025)

Inverse scattering for Schrödinger equation in the frequency domain via data-driven reduced order modeling. - Andreas Tataris; Tristan van Leeuwen; Alexander V. Mamonov (CoRR, 2025)

Phasebook: A Survey of Selected Open Problems in Phase Retrieval. - Marc Allain; Selin Aslan; Wim Coene; Sjoerd Dirksen; Jonathan Dong; Julien Flamant; Mark A. Iwen; Felix Krahmer; Tristan van Leeuwen; Oleh Melnyk; Andreas Menzel; Allard P. Mosk; et al. (CoRR, 2025)