1 code implementation • NeurIPS Workshop DLDE 2021 • Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister
We present a multigrid-in-channels (MGIC) approach that tackles the quadratic growth of the number of parameters with respect to the number of channels in standard convolutional neural networks (CNNs).
no code implementations • 11 Jun 2020 • Jonathan Ephrath, Lars Ruthotto, Eran Treister
We present a multigrid approach that combats the quadratic growth of the number of parameters with respect to the number of channels in standard convolutional neural networks (CNNs).
no code implementations • 29 Oct 2019 • Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister
In practice, the input data and the hidden features consist of a large number of channels, which in most CNNs are fully coupled by the convolution operators.
no code implementations • 15 Apr 2019 • Jonathan Ephrath, Lars Ruthotto, Eldad Haber, Eran Treister
Convolutional Neural Networks (CNNs) filter the input data using spatial convolution operators with compact stencils.