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LED: Latent Variable-based Estimation of Density
[article]
2022
arXiv
pre-print
Modern generative models are roughly divided into two main categories: (1) models that can produce high-quality random samples, but cannot estimate the exact density of new data points and (2) those that provide exact density estimation, at the expense of sample quality and compactness of the latent space. In this work we propose LED, a new generative model closely related to GANs, that allows not only efficient sampling but also efficient density estimation. By maximizing log-likelihood on the
arXiv:2206.11563v1
fatcat:w7v4wlollrglpo5fyquflimpl4