12 citations · 24 across the 3 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2019
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…
cs.LG2017★ 12 cited
A Universal Marginalizer for Amortized Inference in Generative Models
Laura Douglas, Iliyan Zarov, Konstantinos Gourgoulias +6
We consider the problem of inference in a causal generative model where the set of available observations differs between data instances. We show how combining samples drawn from t…