Stephan Mandt (University of California, Irvine) Compressing Variational Bayes Recorded January 15, 2021 Abstract: Neural image compression algorithms have recently outperformed their classical counterparts in rate-distortion performance and show great potential to also revolutionize video coding. In this talk, I will show how recent innovations from approximate Bayesian inference and generative modeling can lead to dramatic performance improvements in compression. In particular, I will explain how sequen
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