Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction

@inproceedings{Wong2019TrainingAO,
  title={Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction},
  author={Tak Ming Wong and Matthias Kahl and Peter Haring Bol{\'i}var and Andreas Kolb and Michael M{\"o}ller},
  booktitle={GCPR},
  year={2019}
}
Terahertz (THz) sensing is a promising imaging technology for a wide variety of different applications. Extracting the interpretable and physically meaningful parameters for such applications, however, requires solving an inverse problem in which a model function determined by these parameters needs to be fitted to the measured data. Since the underlying optimization problem is nonconvex and very costly to solve, we propose learning the prediction of suitable parameters from the measured data… 
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