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

May 12, 2022, 1:10 a.m. | Jaime Roquero Gimenez, James Zou

stat.ML updates on arXiv.org arxiv.org

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

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