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Found 3 papers, 1 papers with code
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks
Deep Generative Networks (DGNs) with probabilistic modeling of their output and latent space are currently trained via Variational Autoencoders (VAEs).
Analytical Probability Distributions and EM-Learning for Deep Generative Networks
Deep Generative Networks (DGNs) with probabilistic modeling of their output and latent space are currently trained via Variational Autoencoders (VAEs).
Max-Affine Spline Insights into Deep Generative Networks
We also derive the output probability density mapped onto the generated manifold in terms of the latent space density, which enables the computation of key statistics such as its Shannon entropy.
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