Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems. (arXiv:2206.09104v2 [cs.LG] UPDATED)

Web: http://arxiv.org/abs/2206.09104

We prove fast mixing and characterize the stationary distribution of the
Langevin Algorithm for inverting random weighted DNN generators. This result
extends the work of Hand and Voroninski from efficient inversion to efficient
posterior sampling. In practice, to allow for increased expressivity, we
propose to do posterior sampling in the latent space of a pre-trained
generative model. To achieve that, we train a score-based model in the latent
space of a StyleGAN-2 and we use it to solve inverse problems. …

arxiv lg optimization