Multimodal Generative Models for Compositional Representation Learning

Wu Mike
Wu Mike
Cited by: 0|Bibtex|Views18
Other Links: arxiv.org

Abstract:

As deep neural networks become more adept at traditional tasks, many of the most exciting new challenges concern multimodality---observations that combine diverse types, such as image and text. In this paper, we introduce a family of multimodal deep generative models derived from variational bounds on the evidence (data marginal likelih...More

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