no code implementations • 31 Dec 2023 • Julian B. B. Beckmann, Mick D. Mantle, Andrew J. Sederman, Lynn F. Gladden
Overall, it could be shown that for a vast majority of instances, deep learning clearly outperforms regularization based inversion methods, if the signal is fully or close to fully sampled.
no code implementations • 22 Nov 2023 • Julian B. B. Beckmann, Mick D. Mantle, Andrew J. Sederman, Lynn F. Gladden
The inversion network is applied to simulated NMR signals and the results compared with Tikhonov- and MTGV-regularization.
