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  • Currently displaying 1 - 20 of 186 publications
Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution.
V Corona, AI Aviles-Rivero, N Debroux, CL Guyader, C-B Schönlieb
– Medical image analysis
(2020)
68,
101941
Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction.
J Liu, AI Aviles-Rivero, H Ji, C-B Schönlieb
– Med Image Anal
(2020)
68,
101930
Compressed sensing plus motion (CS + M): A new perspective for improving undersampled MR image reconstruction
AI Aviles-Rivero, N Debroux, G Williams, MJ Graves, C-B Schönlieb
– Medical image analysis
(2020)
68,
101933
Variational regularisation for inverse problems with imperfect forward operators and general noise models
L Bungert, M Burger, Y Korolev, CB Schönlieb
– CoRR
(2020)
36,
125014
Data driven regularization by projection
A Aspri, Y Korolev, O Scherzer
– Inverse Problems
(2020)
36,
125009
Learning the Sampling Pattern for MRI.
F Sherry, M Benning, JC De Los Reyes, MJ Graves, G Maierhofer, G Williams, C-B Schonlieb, MJ Ehrhardt
– IEEE transactions on medical imaging
(2020)
39,
4310
Structural analysis of an $L$-infinity variational problem and relations to distance functions
L Bungert, Y Korolev, M Burger
– Pure and Applied Analysis
(2020)
2,
703
Scanning electron diffraction tomography of strain
R Tovey, DN Johnstone, SM Collins, WRB Lionheart, PA Midgley, M Benning, C-B Schönlieb
– Inverse Problems
(2020)
37,
015003
Preface for the special issue 'Variational methods and effective algorithms for imaging and vision'
CB Schonlieb, M Hintermuller, S Arridge
– Inverse Problems
(2020)
36,
110401
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-supervised Framework for Medical Image Classification
M de Vriendt, P Sellars, AI Aviles-Rivero
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
(2020)
12443,
187
Accelerating variance-reduced stochastic gradient methods
D Driggs, MJ Ehrhardt, CB Schönlieb
– Mathematical Programming
(2020)
1
iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems
C Etmann, R Ke, CB Schonlieb
– IEEE International Workshop on Machine Learning for Signal Processing, MLSP
(2020)
00,
1
Multilevel Sequential Importance Sampling for Rare Event Estimation
F Wagner, J Latz, I Papaioannou, E Ullmann
– SIAM Journal on Scientific Computing
(2020)
42,
A2062
Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification
P Sellars, AI Aviles-Rivero, CB Schonlieb
– IEEE Transactions on Geoscience and Remote Sensing
(2020)
58,
4180
Optical flow analysis reveals that Kinesin-mediated advection impacts the orientation of microtubules in the Drosophila oocyte.
M Drechsler, LF Lang, L Al-Khatib, H Dirks, M Burger, C-B Schönlieb, IM Palacios
– Mol Biol Cell
(2020)
31,
1246
Tomographic reconstruction with spatially varying parameter selection
Y Dong, CB Schönlieb
– Inverse Problems
(2020)
36,
054002
Variational Osmosis for Non-linear Image Fusion.
S Parisotto, L Calatroni, A Bugeau, N Papadakis, C-B Schonlieb
– IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
(2020)
29,
5507
Higher-Order Total Directional Variation: Analysis.
S Parisotto, S Masnou, CB Schönlieb
– SIAM Journal on Imaging Sciences
(2020)
13,
474
Analysis of Artifacts in Shell-Based Image Inpainting: Why They Occur and How to Eliminate Them
LR Hocking, T Holding, C-B Schoenlieb
– Foundations of Computational Mathematics
(2020)
20,
1549
On the Well-posedness of Bayesian Inverse Problems
J Latz
– SIAM-ASA Journal on Uncertainty Quantification
(2020)
8,
451