Publications: Dr Martin Benning
Wang X, Benning M
(
2023
)
.
A lifted Bregman formulation for the inversion of deep neural networks
.
Frontiers in Applied Mathematics and Statistics
vol.
9
,
Benning M, Riis ES
(
2023
)
.
Bregman Methods for Large-Scale Optimization with Applications in Imaging
.
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision
,
Khan A, Alwazzan O, Benning M, Slabaugh G
(
2023
)
.
Sequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Network and Boundary-Based Processing
.
vol.
13586 LNCS
,
Bonnici RS, Benning M, Saitis C
(
2022
)
.
Timbre Transfer with Variational Auto Encoding and Cycle-Consistent Adversarial Networks
.
Conference:
2022 International Joint Conference on Neural Networks (IJCNN)
vol.
00
,
1
-
8
.
Benning M, Celledoni E, Ehrhardt MJ, Owren B, Schönlieb C-B
(
2021
)
.
Deep learning as optimal control problems
.
IFAC-PapersOnLine
vol.
54
,
(
9
)
620
-
623
.
Benning M, Betcke MM, Ehrhardt MJ, Schönlieb C-B
(
2021
)
.
Choose Your Path Wisely: Gradient Descent in a Bregman Distance Framework
.
SIAM Journal on Imaging Sciences
vol.
14
,
(
2
)
814
-
843
.
Benning M, Riis ES
(
2021
)
.
Bregman Methods for Large-Scale Optimisation with Applications in Imaging
.
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging1
-
42
.
Corona V, Benning M, Gladden LF, Reci A, Sederman AJ, Schönliebs CB
(
2021
)
.
Joint phase reconstruction and magnitude segmentation from velocity-encoded MRI data
.
Time-dependent Problems in Imaging and Parameter Identification
,
Tovey R, Johnstone DN, Collins SM, Lionheart WRB, Midgley PA, Benning M, Schönlieb C-B
(
2020
)
.
Scanning electron diffraction tomography of strain
.
Inverse Problems
Sherry F, Benning M, Reyes JCDL, Graves MJ, Maierhofer G, Williams G, Schonlieb C-B, Ehrhardt MJ
(
2020
)
.
Learning the Sampling Pattern for MRI
.
IEEE Transactions on Medical Imaging1
-
1
.
Benning M, Riis ES, Schönlieb C-B
(
2020
)
.
Bregman Itoh–Abe Methods for Sparse Optimisation
.
Journal of Mathematical Imaging and Vision
Benning M, Celledoni E, Ehrhardt M, Owren B, Schhönlieb C-B
(
2019
)
.
Deep learning as optimal control problems: models and numerical methods
.
Journal of Computational Dynamics
vol.
6
,
(
2
)
171
-
198
.
Burger M, Resmerita E, Benning M
(
2019
)
.
An entropic Landweber method for linear ill-posed problems
.
Inverse Problems
Collins SM, MacArthur KE, Longley L, Tovey R, Benning M, Schönlieb CB, Bennett TD, Midgley PA
(
2019
)
.
Phase diagrams of liquid-phase mixing in multi-component metal-organic framework glasses constructed by quantitative elemental nano-tomography
.
APL Materials
vol.
7
,
(
9
)
Corona V, BENNING M, Ehrhardt M, Gladden L, Mair R, Reci A, Sederman A, Reichelt S et al.
(
2019
)
.
Enhancing joint reconstruction and segmentation with non-convex Bregman iteration
.
Inverse Problems
Tovey R, Benning M, Brune C, Lagerwerf MJ, Collins SM, Leary RK, Midgley PA, Schonlieb C-B
(
2019
)
.
Directional sinogram inpainting for limited angle tomography
.
INVERSE PROBLEMS
vol.
35
,
(
2
)
Article
ARTN 024004
,
Benning M, Burger M
(
2018
)
.
Modern regularization methods for inverse problems
.
Acta Numerica
vol.
27
,
1–111
-
1–111
.
Schmidt MF, Benning M, nlieb C-BS
(
2018
)
.
Inverse scale space decomposition
.
Inverse Problems
vol.
34
,
Article
4
,
045008
-
045008
.
Collins SM, Leary RK, Midgley PA, Tovey R, Benning M, Schönlieb C-B, Rez P, Treacy MMJ
(
2017
)
.
Entropic Comparison of Atomic-Resolution Electron Tomography of Crystals and Amorphous Materials
.
Phys. Rev. Lett.
vol.
119
,
(
16
)
166101
-
166101
.
Benning M, Gilboa G, Grah JS, Schönlieb C-B
(
2017
)
.
Learning Filter Functions in Regularisers by Minimising Quotients
.
Conference:
Scale Space and Variational Methods in Computer Vision (SSVM) 2017511
-
523
.
Benning M, Möller M, Nossek RZ, Burger M, Cremers D, Gilboa G, Schönlieb C-B
(
2017
)
.
Nonlinear Spectral Image Fusion
.
Conference:
Scale Space and Variational Methods in Computer Vision (SSVM) 201741
-
53
.
Benning M, Betcke MM, Ehrhardt MJ, Schönlieb C-B
(
2017
)
.
Gradient descent in a generalised Bregman distance framework
.
Geometric Numerical Integration and its Applications
.
Editors:
Quispel, GRW, Bader, P, McLaren, DI, Tagami, D et al.
,
vol.
74
,
40
-
45
.
Ramskill NP, Bush I, Sederman AJ, Mantle MD, Benning M, Anger BC, Appel M, Gladden LF
(
2016
)
.
Fast imaging of laboratory core floods using 3D compressed sensing RARE MRI
.
Journal of Magnetic Resonance
vol.
270
,
187
-
197
.
Benning M, Gilboa G, Schönlieb C-B
(
2016
)
.
Learning parametrised regularisation functions via quotient minimisation
.
PAMM
vol.
16
,
Article
1
,
933
-
936
.
Benning M, Knoll F, Schönlieb C-B, Valkonen T
(
2016
)
.
Preconditioned ADMM with Nonlinear Operator Constraint
.
117
-
126
.
Harbou EV, Fabich HT, Benning M, Tayler AB, Sederman AJ, Gladden LF, Holland DJ
(
2015
)
.
Quantitative mapping of chemical compositions with MRI using compressed sensing
.
Journal of Magnetic Resonance
vol.
261
,
27
-
37
.
Möller M, Benning M, Schönlieb C-B, Cremers D
(
2015
)
.
Variational Depth From Focus Reconstruction
.
IEEE Transactions on Image Processing
vol.
24
,
Article
12
,
5369
-
5378
.
Saghi Z, Benning M, Leary R, Macias-Montero M, Borras A, Midgley PA
(
2015
)
.
Reduced-dose and high-speed acquisition strategies for multi-dimensional electron microscopy
.
Advanced Structural and Chemical Imaging
vol.
1
,
Article
1
,
7
-
7
.
Heck C, Benning M, Modersitzki J
(
2015
)
.
Joint Registration and Parameter Estimation of T1 Relaxation Times Using Variable Flip Angles
.
215
-
220
.
Fabich HT, Benning M, Sederman AJ, Holland DJ
(
2014
)
.
Ultrashort echo time (UTE) imaging using gradient pre-equalization and compressed sensing
.
Journal of Magnetic Resonance
vol.
245
,
116
-
124
.
Tayler AB, Benning M, Sederman AJ, Holland DJ, Gladden LF
(
2014
)
.
Ultrafast magnetic-resonance-imaging velocimetry of liquid-liquid systems: Overcoming chemical-shift artifacts using compressed sensing
.
Phys. Rev. E
vol.
89
,
(
6
)
063009
-
063009
.
Benning M, Gladden L, Holland D, Schönlieb C-B, Valkonen T
(
2014
)
.
Phase reconstruction from velocity-encoded MRI measurements – A survey of sparsity-promoting variational approaches
.
Journal of Magnetic Resonance
vol.
238
,
26
-
43
.
Benning M, Burger M
(
2013
)
.
Ground states and singular vectors of convex variational regularization methods
.
Methods and Applications of Analysis
vol.
20
,
Article
4
,
295
-
334
.
Burger M, Möller M, Benning M, Osher S
(
2013
)
.
An adaptive inverse scale space method for compressed sensing
.
Mathematics of Computation
vol.
82
,
Article
281
,
269
-
299
.
Benning M, Brune C, Burger M, Müller J
(
2013
)
.
Higher-Order TV Methods—Enhancement via Bregman Iteration
.
Journal of Scientific Computing
vol.
54
,
Article
2
,
269
-
310
.
Benning M, Calatroni L, Düring B, Schönlieb C-B
(
2013
)
.
A Primal-Dual Approach for a Total Variation Wasserstein Flow
.
413
-
421
.
Benning M, Kösters T, Lamare F
(
2012
)
.
Combined correction and reconstruction methods
.
Correction Techniques in Emission Tomography
,
Editors:
Dawood, M, Jiang, X, Schäfers, K
,
CRC Press
Engbers R, Benning M, Heins P, Schäfers K, Burger M
(
2011
)
.
Sparse recovery in myocardial blood flow quantification via PET
.
2011 IEEE Nuclear Science Symposium Conference Record
.
3742
-
3744
.
Benning M, Burger M
(
2011
)
.
Error estimates for general fidelities
.
Electronic Transactions on Numerical Analysis
vol.
38
,
Article
44-68
,
77
-
77
.
Benning M, Burger M
(
2011
)
.
Error estimates for general fidelities
.
Electronic Transactions on Numerical Analysis
vol.
38
,
44
-
68
.
Benning M
(
2011
)
.
Singular Regularization of Inverse Problems: Bregman Distances and their Applications to Variational Frameworks with Singular Regularization Energies
.
Benning M, Heins P, Burger M
(
2010
)
.
A Solver for Dynamic PET Reconstructions based on Forward-Backward-Splitting
.
AIP Conference Proceedings
.
vol.
1281
,
1967
-
1970
.
Benning M, Kösters T, Wübbeling F, Schäfers K, Burger M
(
2008
)
.
A nonlinear variational method for improved quantification of myocardial blood flow using dynamic H215O PET
.
2008 IEEE Nuclear Science Symposium Conference Record
.
4472
-
4477
.