1 citations · 2 across the 3 of their papers we have counts for
4 papers
Masking schemes for universal marginalisers
Divya Gautam, Maria Lomeli, Kostis Gourgoulias +2
We consider the effect of structure-agnostic and structure-dependent masking schemes when training a universal marginaliser (arXiv:1711.00695) in order to learn conditional distrib…
Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs
Robert Walecki, Kostis Gourgoulias, Adam Baker +7
Probabilistic programming languages (PPLs) are powerful modelling tools which allow to formalise our knowledge about the world and reason about its inherent uncertainty. Inference…
Universal Marginalizer for Amortised Inference and Embedding of Generative Models
Robert Walecki, Albert Buchard, Kostis Gourgoulias +6
Probabilistic graphical models are powerful tools which allow us to formalise our knowledge about the world and reason about its inherent uncertainty. There exist a considerable nu…
General Bayesian inference schemes in infinite mixture models
Maria Lomeli
Bayesian statistical models allow us to formalise our knowledge about the world and reason about our uncertainty, but there is a need for better procedures to accurately encode its…