Anna Andrle, Nando Farchmin, Paul Hagemann, Sebastian Heidenreich, Victor Soltwisch, Gabriele Steidl. Invertible Neural Networks Versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence. In Abderrahim Elmoataz, Jalal Fadili, Yvain Quéau, Julien Rabin, Loïc Simon, editors, Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Virtual Event, May 16-20, 2021, Proceedings. Volume 12679 of Lecture Notes in Computer Science, pages 528-539, Springer, 2021. [doi]
@inproceedings{AndrleFHHSS21,
title = {Invertible Neural Networks Versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence},
author = {Anna Andrle and Nando Farchmin and Paul Hagemann and Sebastian Heidenreich and Victor Soltwisch and Gabriele Steidl},
year = {2021},
doi = {10.1007/978-3-030-75549-2_42},
url = {https://doi.org/10.1007/978-3-030-75549-2_42},
researchr = {https://researchr.org/publication/AndrleFHHSS21},
cites = {0},
citedby = {0},
pages = {528-539},
booktitle = {Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Virtual Event, May 16-20, 2021, Proceedings},
editor = {Abderrahim Elmoataz and Jalal Fadili and Yvain Quéau and Julien Rabin and Loïc Simon},
volume = {12679},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-030-75549-2},
}