A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems
Simon Pfreundschuh et al.
Model code and software
typhon - Tools for atmospheric researchJohn Mrziglod, Lukas Kluft, Oliver Lemke, Gerrit Holl, Simon Pfreundschuh, Richard Larsson, Takayoshi Yamada, and Jakob Doerr https://doi.org/10.5281/zenodo.1300319
A novel neural-network-based retrieval method is proposed that combines the flexibility and computational efficiency of machine learning retrievals with the consistent treatment of uncertainties of Bayesian methods. Numerical experiments are presented that show the consistency of the proposed method with the Bayesian formulation as well as its ability to represent non-Gaussian retrieval errors. With this, the proposed method overcomes important limitations of traditional methods.
A novel neural-network-based retrieval method is proposed that combines the flexibility and...