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Stochastic Normalizing Flows for Inverse Problems: A Markov Chains Viewpoint

  • Published:2022-09-28 Issue:3 Volume:10 Page:1162-1190
  • ISSN:2166-2525
  • Container-title:SIAM/ASA Journal on Uncertainty Quantification
  • language:en
  • Short-container-title:SIAM/ASA J. Uncertainty Quantification

Author:

Hagemann Paul1,Hertrich Johannes1,Steidl Gabriele1

Affiliation:

1. TU Berlin, D-10587 Berlin, Germany (, , ).

Funder

Deutsche Forschungsgemeinschaft

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Discrete Mathematics and Combinatorics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reduced-order model-based variational inference with normalizing flows for Bayesian elliptic inverse problems;Journal of Computational and Applied Mathematics;2024-05

2. Formal Management-Specifying Approach for Model-Based Safety Assessment;Journal of Systems Engineering and Electronics;2023-12

3. Self-Supervised Deep Learning for Image Reconstruction: A Langevin Monte Carlo Approach;SIAM Journal on Imaging Sciences;2023-11-30

4. WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution;SIAM Journal on Imaging Sciences;2023-07-12

5. Solving Stochastic Inverse Problems with Stochastic BayesFlow;2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM);2023-06-28
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