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Thomas Möllenhoff
Thomas Möllenhoff
Sonstige NamenThomas Moellenhoff
Research Scientist, RIKEN AIP
Bestätigte E-Mail-Adresse bei postman.riken.jp - Startseite
Titel
Zitiert von
Zitiert von
Jahr
The primal-dual hybrid gradient method for semiconvex splittings
T Möllenhoff, E Strekalovskiy, M Moeller, D Cremers
SIAM Journal on Imaging Sciences 8 (2), 827-857, 2015
722015
Sublabel-accurate relaxation of nonconvex energies
T Möllenhoff, E Laude, M Moeller, J Lellmann, D Cremers
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
492016
Fight ill-posedness with ill-posedness: Single-shot variational depth super-resolution from shading
B Haefner, Y Quéau, T Möllenhoff, D Cremers
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
452018
Proximal backpropagation
T Frerix, T Möllenhoff, M Moeller, D Cremers
International Conference on Learning Representations (ICLR), 2017
412017
Sublabel-accurate convex relaxation of vectorial multilabel energies
E Laude, T Möllenhoff, M Moeller, J Lellmann, D Cremers
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
302016
Low rank priors for color image regularization
T Möllenhoff, E Strekalovskiy, M Möller, D Cremers
Energy Minimization Methods in Computer Vision and Pattern Recognition: 10th …, 2015
282015
Sublabel-accurate discretization of nonconvex free-discontinuity problems
T Möllenhoff, D Cremers
Proceedings of the IEEE International Conference on Computer Vision, 1183-1191, 2017
222017
Controlling neural networks via energy dissipation
M Moeller, T Mollenhoff, D Cremers
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
202019
SAM as an Optimal Relaxation of Bayes
T Möllenhoff, ME Khan
arXiv preprint arXiv:2210.01620, 2022
142022
Lifting vectorial variational problems: a natural formulation based on geometric measure theory and discrete exterior calculus
T Mollenhoff, D Cremers
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
142019
Lifting the convex conjugate in Lagrangian relaxations: a tractable approach for continuous Markov random fields
H Bauermeister, E Laude, T Möllenhoff, M Moeller, D Cremers
SIAM Journal on Imaging Sciences 15 (3), 1253-1281, 2022
92022
Combinatorial preconditioners for proximal algorithms on graphs
T Möllenhoff, Z Ye, T Wu, D Cremers
International Conference on Artificial Intelligence and Statistics, 38-47, 2018
62018
Efficient convex optimization for minimal partition problems with volume constraints
T Möllenhoff, C Nieuwenhuis, E Töppe, D Cremers
Energy Minimization Methods in Computer Vision and Pattern Recognition: 9th …, 2013
52013
Flat Metric Minimization with Applications in Generative Modeling
T Möllenhoff, D Cremers
International Conference on Machine Learning (ICML), 4626--4635, 2019
32019
Sublabel-accurate multilabeling meets product label spaces
Z Ye, B Haefner, Y Quéau, T Möllenhoff, D Cremers
DAGM German Conference on Pattern Recognition, 3-17, 2021
22021
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning
Z Ye, T Möllenhoff, T Wu, D Cremers
International Conference on Artificial Intelligence and Statistics, 657-668, 2020
22020
The Lie-Group Bayesian Learning Rule
EM Kiral, T Moellenhoff, ME Khan
International Conference on Artificial Intelligence and Statistics, 3331-3352, 2023
12023
A Cutting-Plane Method for Sublabel-Accurate Relaxation of Problems with Product Label Spaces
Z Ye, B Haefner, Y Quéau, T Möllenhoff, D Cremers
International Journal of Computer Vision 131 (1), 346-362, 2023
12023
The Memory Perturbation Equation: Understanding Model's Sensitivity to Data
P Nickl, L Xu, D Tailor, T Möllenhoff, ME Khan
arXiv preprint arXiv:2310.19273, 2023
2023
Model Merging by Uncertainty-Based Gradient Matching
N Daheim, T Möllenhoff, EM Ponti, I Gurevych, ME Khan
arXiv preprint arXiv:2310.12808, 2023
2023
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