Preprints 2019
- Nr. 65 Monotonicity of escape probabilities for branching random walks on Zd
A. Tzioufas
[Download PDF][arxiv.org]
- Nr. 64 Sparse regularization of inverse problems by operator-dapted frame thresholding
J. Frikel, M. Haltmeier
[Download PDF][arxiv.org]
- Nr. 63 Projection-Based 2.5D U-net architecture for fast volumetric segmentation
C. Angermann, M. Haltmeier, R. Steiger, S. Pereverzyev Jr., E. Gizewski
[Download PDF][arxiv.org]
- Nr. 62 Explicit inversion formulas for the two-dimensional wave equation from Neuman Traces
F. Dreier, M. Haltmeier
[Download PDF][arxiv.org]
- Nr. 61 Analysis of the block coordinate descent method for linear Ill-Posed problems
S. Rabanser, L. Neumann, M. Haltmeier
[Download PDF][arxiv.org]
- Nr. 60 Sparse synthesis regularization with deep neural networks
D. Obmann, J. Schwab, M. Haltmeier
[Download PDF][arxiv.org]
- Nr. 59 Projection-Based 2.5D U-net architecture for fast volumetric segmentation
C. Angermann, M. Haltmeier, R. Steiger, S. Pereverzyev Jr., E. Gizewski
[Download PDF][arxiv.org]
- Nr. 58 NETT regularization for compressed sensing photoacoustic tomography
S. Antholzer, J. Schwab, J.Bauer-Marschallinger, P. Burgholzer, M. Haltmeier
[Download PDF][arxiv.org]
- Nr. 57 Deep learning versus -minimization for compressed sensing photoacoustic tomography
S. Antholzer, J. Schwab, M. Haltmeier
[Download PDF][arxiv.org]
- Nr. 56 Photoacoustic tomography with direction dependent data: An exact series reconstruction approach
G. Zangerl, S. Moon, M. Haltmeier
[Download PDF][arxiv.org]
- Nr. 55 Big in Japan: Regularizing networks for solving inverse problems
J. Schwab, S. Antholzer, M. Haltmeier
[Download PDF][arxiv.org]