2018
Invertibility of Convolutional Generative Networks from Partial Measurements
NeurIPS 2018poster
In this work, we present new theoretical results on convolutional generative neural networks, in particular their invertibility (i.e., the recovery of input latent code given the network output). The study of network inversion problem is motivated by image inpainting and the mode collapse problem in…