@misc{schiller_model_inversion_2007, 
author={Schiller, H.},
title={Model inversion by parameter fit using NN emulating the forward model - Evaluation of indirect measurements},
year={2007},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.neunet.2007.04.022},
abstract = {This paper shows how NNs can be used to improve inversion accuracy by minimizing the sum of error squares. The procedure is very fast as it takes advantage of the Jacobian which is a byproduct of the NN calculation. An example from remote sensing is shown. It is also possible to take into account a non-diagonal covariance matrix of the measurement to derive the covariance matrix of the retrieved parameters.},
note = {Online available at: \url{https://doi.org/10.1016/j.neunet.2007.04.022} (DOI). Schiller, H.: Model inversion by parameter fit using NN emulating the forward model - Evaluation of indirect measurements. Neural networks. 2007. vol. 20, no. 4, 479-483. DOI: 10.1016/j.neunet.2007.04.022}}