117 citations · 323 across the 20 of their papers we have counts for
3 papers · 1 filter
Learning Direct Optimization for Scene Understanding
Lukasz Romaszko, Christopher K. I. Williams, John Winn
We develop a Learning Direct Optimization (LiDO) method for the refinement of a latent variable model that describes input image x. Our goal is to explain a single image x with an…
Inverting Supervised Representations with Autoregressive Neural Density Models
Charlie Nash, Nate Kushman, Christopher K. I. Williams
We present a method for feature interpretation that makes use of recent advances in autoregressive density estimation models to invert model representations. We train generative in…
Autoencoders and Probabilistic Inference with Missing Data: An Exact Solution for The Factor Analysis Case
Christopher K. I. Williams, Charlie Nash, Alfredo Nazábal
Latent variable models can be used to probabilistically "fill-in" missing data entries. The variational autoencoder architecture (Kingma and Welling, 2014; Rezende et al., 2014) in…