A Unified f-divergence Framework Generalizing VAE and GAN. (arXiv:2205.05214v1 [stat.ML])

Web: http://arxiv.org/abs/2205.05214

Developing deep generative models that flexibly incorporate diverse measures
of probability distance is an important area of research. Here we develop an
unified mathematical framework of f-divergence generative model, f-GM, that
incorporates both VAE and f-GAN, and enables tractable learning with general
f-divergences. f-GM allows the experimenter to flexibly design the f-divergence
function without changing the structure of the networks or the learning
procedure. f-GM jointly models three components: a generator, a inference
network and a density estimator. Therefore it …

arxiv divergence framework gan ml