166 citations · 507 across the 29 of their papers we have counts for
4 papers · 1 filter
Lossy Image Compression with Conditional Diffusion Models
Ruihan Yang, Stephan Mandt
This paper outlines an end-to-end optimized lossy image compression framework using diffusion generative models. The approach relies on the transform coding paradigm, where an imag…
Diffusion Probabilistic Modeling for Video Generation
Ruihan Yang, Prakhar Srivastava, Stephan Mandt
Denoising diffusion probabilistic models are a promising new class of generative models that mark a milestone in high-quality image generation. This paper showcases their ability t…
SC2 Benchmark: Supervised Compression for Split Computing
Yoshitomo Matsubara, Ruihan Yang, Marco Levorato +1
With the increasing demand for deep learning models on mobile devices, splitting neural network computation between the device and a more powerful edge server has become an attract…
An Introduction to Neural Data Compression
Yibo Yang, Stephan Mandt, Lucas Theis
Neural compression is the application of neural networks and other machine learning methods to data compression. Recent advances in statistical machine learning have opened up new…