22 citations · 92 across the 18 of their papers we have counts for
4 papers · 1 filter
Statistical Model Criticism of Variational Auto-Encoders
Claartje Barkhof, Wilker Aziz
We propose a framework for the statistical evaluation of variational auto-encoders (VAEs) and test two instances of this framework in the context of modelling images of handwritten…
Sparse Communication via Mixed Distributions
António Farinhas, Wilker Aziz, Vlad Niculae +1
Neural networks and other machine learning models compute continuous representations, while humans communicate mostly through discrete symbols. Reconciling these two forms of commu…
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity
Gonçalo M. Correia, Vlad Niculae, Wilker Aziz +1
Training neural network models with discrete (categorical or structured) latent variables can be computationally challenging, due to the need for marginalization over large or comb…
Latent Transformations for Discrete-Data Normalising Flows
Rob Hesselink, Wilker Aziz
Normalising flows (NFs) for discrete data are challenging because parameterising bijective transformations of discrete variables requires predicting discrete/integer parameters. Ha…