<ul><li>Variational Autoencoders (VAEs) are a popular framework for unsupervised learning and data generation.</li><li>A study focused on the Soft-IntroVAE (S-IntroVAE) and investigated the implication of incorporating a multimodal and learnable prior into the framework.</li><li>The study formulated the prior as a third player and showed that it is an effective way for prior learning, sharing the Nash Equilibrium with the vanilla S-IntroVAE.</li><li>Experiments demonstrated the benefit of prior learning in S-IntroVAE in generation and representation learning on benchmark datasets.</li></ul>

Prior Learning in Introspective VAEs

Discover more