Variational Information Bottleneck for Unsupervised Clustering: Deep Gaussian Mixture Embedding

ICLR 2020 Yigit UgurGeorge ArvanitakisAbdellatif Zaidi

In this paper, we develop an unsupervised generative clustering framework that combines the Variational Information Bottleneck and the Gaussian Mixture Model. Specifically, in our approach, we use the Variational Information Bottleneck method and model the latent space as a mixture of Gaussians... (read more)

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