Probabilistic Programming with Programmable Variational Inference

Probabilistic Programming with Programmable Variational Inference

Compared to the wide array of advanced Monte Carlo methods supported by modern probabilistic programming languages (PPLs), PPL support for variational inference (VI) is underdeveloped: users are typically limited to a small selection of predefined variational objectives and gradient estimators, whic...

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Bibliographic Details
Main Authors: Becker, McCoy R., Lew, Alexander K., Wang, Xiaoyan, Ghavami, Matin, Huot, Mathieu, Rinard, Martin C., Mansinghka, Vikash K.
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Association for Computing Machinery 2024
Online Access:https://hdl.handle.net/1721.1/155517

Internet

https://hdl.handle.net/1721.1/155517

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