59 citations · 240 across the 11 of their papers we have counts for
4 papers · 1 filter
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC
Priyank Jaini, Didrik Nielsen, Max Welling
Hybrid Monte Carlo is a powerful Markov Chain Monte Carlo method for sampling from complex continuous distributions. However, a major limitation of HMC is its inability to be appli…
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom +2
Normalizing flows and variational autoencoders are powerful generative models that can represent complicated density functions. However, they both impose constraints on the models:…
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow
Didrik Nielsen, Ole Winther
Flow models have recently made great progress at modeling ordinal discrete data such as images and audio. Due to the continuous nature of flow models, dequantization is typically a…
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient
Aaron Mishkin, Frederik Kunstner, Didrik Nielsen +2
Uncertainty estimation in large deep-learning models is a computationally challenging task, where it is difficult to form even a Gaussian approximation to the posterior distributio…