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Probabilistic Programming

Probabilistic programming languages are designed to describe probabilistic models and then perform inference in those models. PPLs are closely related to graphical models and Bayesian networks, but are more expressive and flexible.

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Papers

Showing 161170 of 273 papers

TitleStatusHype
Deployable probabilistic programming0
Exploring Bayesian approaches to eQTL mapping through probabilistic programmingCode0
Automatic Reparameterisation of Probabilistic ProgramsCode0
Hijacking Malaria Simulators with Probabilistic Programming0
Rotation Invariant Householder Parameterization for Bayesian PCACode0
Modular Deep Probabilistic ProgrammingCode0
A Bayesian Monte Carlo approach for predicting the spread of infectious diseasesCode0
Reversible Jump Probabilistic ProgrammingCode0
The Random Conditional Distribution for Higher-Order Probabilistic Inference0
Applying Probabilistic Programming to Affective ComputingCode0
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