335 citations · 499 across the 11 of their papers we have counts for
5 papers · 1 filter
Latent Discretization for Continuous-time Sequence Compression
Ricky T. Q. Chen, Matthew Le, Matthew Muckley +2
Neural compression offers a domain-agnostic approach to creating codecs for lossy or lossless compression via deep generative models. For sequence compression, however, most deep s…
An optimal control perspective on diffusion-based generative modeling
Julius Berner, Lorenz Richter, Karen Ullrich
We establish a connection between stochastic optimal control and generative models based on stochastic differential equations (SDEs), such as recently developed diffusion probabili…
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Yangjun Ruan, Karen Ullrich, Daniel Severo +5
Latent variable models have been successfully applied in lossless compression with the bits-back coding algorithm. However, bits-back suffers from an increase in the bitrate equal…
Neural Communication Systems with Bandwidth-limited Channel
Karen Ullrich, Fabio Viola, Danilo Jimenez Rezende
Reliably transmitting messages despite information loss due to a noisy channel is a core problem of information theory. One of the most important aspects of real world communicatio…
Differentiable probabilistic models of scientific imaging with the Fourier slice theorem
Karen Ullrich, Rianne van den Berg, Marcus Brubaker +2
Scientific imaging techniques such as optical and electron microscopy and computed tomography (CT) scanning are used to study the 3D structure of an object through 2D observations.…