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Thomas Möllenhoff
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2020 – today
- 2024
- [c20]Nico Daheim, Thomas Möllenhoff, Edoardo M. Ponti, Iryna Gurevych, Mohammad Emtiyaz Khan:
Model Merging by Uncertainty-Based Gradient Matching. ICLR 2024 - [c19]Etash Kumar Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Eugène Ndiaye:
Conformal Prediction via Regression-as-Classification. ICLR 2024 - [c18]Yuesong Shen, Nico Daheim, Bai Cong, Peter Nickl, Gian Maria Marconi, Clement Bazan, Rio Yokota, Iryna Gurevych, Daniel Cremers, Mohammad Emtiyaz Khan, Thomas Möllenhoff:
Variational Learning is Effective for Large Deep Networks. ICML 2024 - [i18]Yuesong Shen, Nico Daheim, Bai Cong, Peter Nickl, Gian Maria Marconi, Clement Bazan, Rio Yokota, Iryna Gurevych, Daniel Cremers, Mohammad Emtiyaz Khan, Thomas Möllenhoff:
Variational Learning is Effective for Large Deep Networks. CoRR abs/2402.17641 (2024) - [i17]Etash Kumar Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Eugène Ndiaye:
Conformal Prediction via Regression-as-Classification. CoRR abs/2404.08168 (2024) - 2023
- [j3]Zhenzhang Ye
, Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers
A Cutting-Plane Method for Sublabel-Accurate Relaxation of Problems with Product Label Spaces. Int. J. Comput. Vis. 131(1): 346-362 (2023) - [c17]Eren Mehmet Kiral, Thomas Möllenhoff, Mohammad Emtiyaz Khan:
The Lie-Group Bayesian Learning Rule. AISTATS 2023: 3331-3352 - [c16]Thomas Möllenhoff, Mohammad Emtiyaz Khan:
SAM as an Optimal Relaxation of Bayes. ICLR 2023 - [c15]Peter Nickl, Lu Xu, Dharmesh Tailor, Thomas Möllenhoff, Mohammad Emtiyaz Khan:
The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data. NeurIPS 2023 - [i16]Eren Mehmet Kiral, Thomas Möllenhoff, Mohammad Emtiyaz Khan:
The Lie-Group Bayesian Learning Rule. CoRR abs/2303.04397 (2023) - [i15]Nico Daheim, Thomas Möllenhoff, Edoardo Maria Ponti, Iryna Gurevych, Mohammad Emtiyaz Khan:
Model Merging by Uncertainty-Based Gradient Matching. CoRR abs/2310.12808 (2023) - [i14]Peter Nickl, Lu Xu, Dharmesh Tailor, Thomas Möllenhoff, Mohammad Emtiyaz Khan:
The Memory Perturbation Equation: Understanding Model's Sensitivity to Data. CoRR abs/2310.19273 (2023) - 2022
- [j2]Hartmut Bauermeister
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. SIAM J. Imaging Sci. 15(3): 1253-1281 (2022) - [c14]Hannah Dröge
Non-Smooth Energy Dissipating Networks. ICIP 2022: 3281-3285 - [i13]Thomas Möllenhoff, Mohammad Emtiyaz Khan:
SAM as an Optimal Relaxation of Bayes. CoRR abs/2210.01620 (2022) - 2021
- [c13]Zhenzhang Ye, Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff
Sublabel-Accurate Multilabeling Meets Product Label Spaces. GCPR 2021: 3-17 - [i12]Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. CoRR abs/2107.06028 (2021) - 2020
- [b1]Thomas Möllenhoff:
Efficient Lifting Methods for Variational Problems. Technical University of Munich, Germany, 2020 - [c12]Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers:
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning. AISTATS 2020: 657-668 - [i11]Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers:
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning. CoRR abs/2002.12236 (2020)
2010 – 2019
- 2019
- [c11]Thomas Möllenhoff
Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus. CVPR 2019: 11117-11126 - [c10]Michael Möller, Thomas Möllenhoff
Controlling Neural Networks via Energy Dissipation. ICCV 2019: 3255-3264 - [c9]Thomas Möllenhoff, Daniel Cremers:
Flat Metric Minimization with Applications in Generative Modeling. ICML 2019: 4626-4635 - [i10]Michael Möller, Thomas Möllenhoff, Daniel Cremers:
Controlling Neural Networks via Energy Dissipation. CoRR abs/1904.03081 (2019) - [i9]Thomas Möllenhoff, Daniel Cremers:
Lifting Vectorial Variational Problems: A Natural Formulation based on Geometric Measure Theory and Discrete Exterior Calculus. CoRR abs/1905.00851 (2019) - [i8]Thomas Möllenhoff, Daniel Cremers:
Flat Metric Minimization with Applications in Generative Modeling. CoRR abs/1905.04730 (2019) - [i7]Pierre Bréchet, Tao Wu, Thomas Möllenhoff, Daniel Cremers:
Informative GANs via Structured Regularization of Optimal Transport. CoRR abs/1912.02160 (2019) - 2018
- [c8]Thomas Möllenhoff, Zhenzhang Ye, Tao Wu, Daniel Cremers:
Combinatorial Preconditioners for Proximal Algorithms on Graphs. AISTATS 2018: 38-47 - [c7]Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff
Fight Ill-Posedness With Ill-Posedness: Single-Shot Variational Depth Super-Resolution From Shading. CVPR 2018: 164-174 - [c6]Thomas Frerix, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Proximal Backpropagation. ICLR (Poster) 2018 - [i6]Thomas Möllenhoff, Zhenzhang Ye, Tao Wu, Daniel Cremers:
Combinatorial Preconditioners for Proximal Algorithms on Graphs. CoRR abs/1801.05413 (2018) - 2017
- [c5]Thomas Möllenhoff
Sublabel-Accurate Discretization of Nonconvex Free-Discontinuity Problems. ICCV 2017: 1192-1200 - [i5]Thomas Frerix, Thomas Möllenhoff, Michael Möller, Daniel Cremers:
Proximal Backpropagation. CoRR abs/1706.04638 (2017) - 2016
- [c4]Thomas Möllenhoff
Sublabel-Accurate Relaxation of Nonconvex Energies. CVPR 2016: 3948-3956 - [c3]Emanuel Laude
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. ECCV (1) 2016: 614-627 - [i4]Emanuel Laude, Thomas Möllenhoff, Michael Möller, Jan Lellmann, Daniel Cremers:
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. CoRR abs/1604.01980 (2016) - [i3]Thomas Möllenhoff, Daniel Cremers:
Precise Relaxation of the Mumford-Shah Functional. CoRR abs/1611.06987 (2016) - 2015
- [j1]Thomas Möllenhoff
The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings. SIAM J. Imaging Sci. 8(2): 827-857 (2015) - [i2]Thomas Möllenhoff, Emanuel Laude, Michael Möller, Jan Lellmann, Daniel Cremers:
Sublabel-Accurate Relaxation of Nonconvex Energies. CoRR abs/1512.01383 (2015) - 2014
- [c2]Thomas Möllenhoff
Low Rank Priors for Color Image Regularization. EMMCVPR 2014: 126-140 - [i1]Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Möller, Daniel Cremers:
The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings. CoRR abs/1407.1723 (2014) - 2013
- [c1]Thomas Möllenhoff
Efficient Convex Optimization for Minimal Partition Problems with Volume Constraints. EMMCVPR 2013: 94-107
Coauthor Index
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last updated on 2024-09-05 02:08 CEST by the dblp team
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