Jürgen Cito

Probabilistic Programming with Programmable Divide-Conquer-Combine Inference on Modern Hardware

Universal probabilistic programming languages (PPLs) enable the specification of models with stochastic support structure. Posterior inference is notoriously hard for this class of models and remains difficult to accelerate on modern hardware. In response to these challenges, we...