Dennis Forster — accepted AI-conference papers

2023

The ELBO of Variational Autoencoders Converges to a Sum of Entropies

Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke

AISTATS 2023poster

The central objective function of a variational autoencoder (VAE) is its variational lower bound (the ELBO). Here we show that for standard (i.e., Gaussian) VAEs the ELBO converges to a value given by the sum of three entropies: the (negative) entropy of the prior distribution, the expected (negativ…

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2018

Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means

Dennis Forster, Jörg Lücke

AISTATS 2018poster

One iteration of standard k-means (i.e., Lloyd’s algorithm) or standard EM for Gaussian mixture models (GMMs) scales linearly with the number of clusters C, data points N, and data dimensionality D. In this study, we explore whether one iteration of k-means or EM for GMMs can scale sublinearly with…

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