Probabilistic Programming with Stochastic Probabilities

Probabilistic Programming with Stochastic Probabilities

We present a new approach to the design and implementation of probabilistic programming languages (PPLs), based on the idea of stochastically estimating the probability density ratios necessary for probabilistic inference. By relaxing the usual PPL design constraint that these densities be compute...

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Bibliographic Details
Main Authors: Lew, Alexander K., Ghavamizadeh, Matin, Rinard, Martin C., Mansinghka, Vikash K.
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:English
Published: ACM 2023
Online Access:https://hdl.handle.net/1721.1/151094

Internet

https://hdl.handle.net/1721.1/151094

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