Learning to reconstruct Germano Differential Filtered Fields with Convolutional Neural Networks for Large Eddy Simulation of Plasma Turbulence

We present a novel method which combines the invertibility of the differential filter of Germano, with convolutional networks to accelerate plasma turbulence simulations. Rather than learning the mapping from coarse-grid LES fields to fine-grid DNS, the proposed method learns the mapping from coarse