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A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation
[article]
2019
arXiv
pre-print
We introduce and demonstrate the variational autoencoder (VAE) for probabilistic non-negative matrix factorisation (PAE-NMF). We design a network which can perform non-negative matrix factorisation (NMF) and add in aspects of a VAE to make the coefficients of the latent space probabilistic. By restricting the weights in the final layer of the network to be non-negative and using the non-negative Weibull distribution we produce a probabilistic form of NMF which allows us to generate new data and
arXiv:1906.05912v1
fatcat:4to4yx5itfcabmafz57mnanha4