Multi-View Networks for Denoising of Arbitrary Numbers of Channels

Jonah Casebeer, Brian Luc, Paris Smaragdis

We propose a set of denoising neural networks capable of operating on an arbitrary number of channels at runtime, irrespective of how many channels they were trained on. We coin th…