• Corpus ID: 202577519

Learned imaging with constraints and uncertainty quantification

@article{Herrmann2019LearnedIW,
  title={Learned imaging with constraints and uncertainty quantification},
  author={F. Herrmann and Ali Siahkoohi and Gabrio Rizzuti},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.06473}
}
We outline new approaches to incorporate ideas from deep learning into wave-based least-squares imaging. The aim, and main contribution of this work, is the combination of handcrafted constraints with deep convolutional neural networks, as a way to harness their remarkable ease of generating natural images. The mathematical basis underlying our method is the expectation-maximization framework, where data are divided in batches and coupled to additional "latent" unknowns. These unknowns are… 
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