1 code implementation • 2 Jun 2020 • Tatiana A. Bubba, Mathilde Galinier, Matti Lassas, Marco Prato, Luca Ratti, Samuli Siltanen
We propose a novel convolutional neural network (CNN), called $\Psi$DONet, designed for learning pseudodifferential operators ($\Psi$DOs) in the context of linear inverse problems.
no code implementations • 28 Jun 2019 • Giorgia Franchini, Mathilde Galinier, Micaela Verucchi
This approach can be of particular interest when the space of the characteristics of the network is notably large or when its full training is highly time-consuming.
