no code implementations • 30 Aug 2023 • Louis Rouillard, Alexandre Le Bris, Thomas Moreau, Demian Wassermann
Given observed data and a probabilistic generative model, Bayesian inference searches for the distribution of the model's parameters that could have yielded the data.
no code implementations • 10 Jun 2022 • Louis Rouillard, Thomas Moreau, Demian Wassermann
Given some observed data and a probabilistic generative model, Bayesian inference aims at obtaining the distribution of a model's latent parameters that could have yielded the data.
no code implementations • ICLR 2022 • Louis Rouillard, Demian Wassermann
Frequently, population studies feature pyramidally-organized data represented using Hierarchical Bayesian Models (HBM) enriched with plates.