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Deep Gaussian mixture models as proposed by Viroli and McLachlan (2019) <doi:10.1007/s11222-017-9793-z> provide a generalization of classical Gaussian mixtures to multiple layers. Each layer contains a set of latent variables that follow a mixture of Gaussian distributions. To avoid overparameterized solutions, dimension reduction is applied at each layer by way of factor models.
Package details |
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Author | Cinzia Viroli, Geoffrey J. McLachlan |
Maintainer | Suren Rathnayake <surenr@gmail.com> |
License | GPL (>= 3) |
Version | 0.2.1 |
URL | https://github.com/suren-rathnayake/deepgmm |
Package repository | View on CRAN |
Installation |
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