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Maximilian Schmidt
Maximilian Schmidt
Researcher of Entrepreneurial Finance, Technische Universität München (TUM)
Verified email at wi.tum.de
Title
Cited by
Cited by
Year
Computed tomography reconstruction using deep image prior and learned reconstruction methods
DO Baguer, J Leuschner, M Schmidt
Inverse Problems 36 (9), 094004, 2020
1632020
LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction
J Leuschner, M Schmidt, DO Baguer, P Maass
Scientific Data 8 (1), 109, 2021
702021
Highly Active N, O Zinc Guanidine Catalysts for the Ring‐Opening Polymerization of Lactide
PM Schäfer, M Fuchs, A Ohligschläger, R Rittinghaus, P McKeown, E Akin, ...
ChemSusChem 10 (18), 3547-3556, 2017
682017
Considering the shareholder perspective: value-based management systems and stock market performance
MS Rapp, D Schellong, M Schmidt, M Wolff
Review of Managerial Science 5, 171-194, 2011
612011
Backfiltration in hemodialyzers with highly permeable membranes: an in vitro and in vivo investigation
M Schmidt, CA Baldamus, W Schoeppe
Blood purification 2 (2), 108-114, 1984
601984
Non-thermal fixed points and solitons in a one-dimensional Bose gas
M Schmidt, S Erne, B Nowak, D Sexty, T Gasenzer
New Journal of Physics 14 (7), 075005, 2012
592012
Supervised non-negative matrix factorization methods for MALDI imaging applications
J Leuschner, M Schmidt, P Fernsel, D Lachmund, T Boskamp, P Maass
Bioinformatics 35 (11), 1940-1947, 2019
532019
The lodopab-ct dataset: A benchmark dataset for low-dose ct reconstruction methods
J Leuschner, M Schmidt, DO Baguer, P Maaß
arXiv preprint arXiv:1910.01113, 2019
482019
Product-state distributions in the dissociative recombination of and
J Semaniak, S Rosen, G Sundström, C Strömholm, S Datz, H Danared, ...
Physical Review A 54 (6), R4617, 1996
481996
Quantitative comparison of deep learning-based image reconstruction methods for low-dose and sparse-angle CT applications
J Leuschner, M Schmidt, PS Ganguly, V Andriiashen, SB Coban, ...
Journal of Imaging 7 (3), 44, 2021
452021
Conditional invertible neural networks for medical imaging
A Denker, M Schmidt, J Leuschner, P Maass
Journal of Imaging 7 (11), 243, 2021
372021
Structural behavior of large-scale I-beams with combined textile and CFRP reinforcement
J Bielak, M Schmidt, J Hegger, F Jesse
Applied Sciences 10 (13), 4625, 2020
352020
Superior catalyst recycling in surfactant based multiphase systems–Quo vadis catalyst complex?
T Pogrzeba, D Müller, M Illner, M Schmidt, Y Kasaka, A Weber, G Wozny, ...
Chemical Engineering and Processing: Process Intensification 99, 155-166, 2016
332016
A novel process concept for the three step Boscalid® synthesis
I Volovych, M Neumann, M Schmidt, G Buchner, JY Yang, J Wölk, ...
RSC advances 6 (63), 58279-58287, 2016
302016
Shear response of members without shear reinforcement—experiments and analysis using shear crack propagation theory (SCPT)
M Schmidt, P Schmidt, S Wanka, M Classen
Applied Sciences 11 (7), 3078, 2021
262021
Micellar enhanced ultrafiltration of a rhodium catalyst
M Schwarze, M Schmidt, LAT Nguyen, A Drews, M Kraume, ...
Journal of membrane science 421, 165-171, 2012
262012
Status of the Sulzer Hexis product development
R Diethelm, M Schmidt, K Honegger, E Batawi
ECS Proceedings Volumes 1999 (1), 60, 1999
231999
Normalizing flows for novelty detection in industrial time series data
M Schmidt, M Simic
arXiv preprint arXiv:1906.06904, 2019
222019
Should I stay, or should I go?–How fund dynamics influence venture capital exit decisions
C Bock, M Schmidt
Review of Financial Economics 27, 68-82, 2015
212015
The limited partnership model in private equity: Deal returns over a fund's life
R Braun, M Schmidt
Center for Entrepreneurial and Financial Studies Working Paper, 2014
212014
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