63 citations · 203 across the 11 of their papers we have counts for
4 papers · 1 filter
Resampled Priors for Variational Autoencoders
Matthias Bauer, Andriy Mnih
We propose Learned Accept/Reject Sampling (LARS), a method for constructing richer priors using rejection sampling with a learned acceptance function. This work is motivated by rec…
Learning Invariances using the Marginal Likelihood
Mark van der Wilk, Matthias Bauer, ST John +1
Generalising well in supervised learning tasks relies on correctly extrapolating the training data to a large region of the input space. One way to achieve this is to constrain the…
Automatic Estimation of Modulation Transfer Functions
Matthias Bauer, Valentin Volchkov, Michael Hirsch +1
The modulation transfer function (MTF) is widely used to characterise the performance of optical systems. Measuring it is costly and it is thus rarely available for a given lens sp…
Meta-Learning Probabilistic Inference For Prediction
Jonathan Gordon, John Bronskill, Matthias Bauer +2
This paper introduces a new framework for data efficient and versatile learning. Specifically: 1) We develop ML-PIP, a general framework for Meta-Learning approximate Probabilistic…