Probabilistic programming with programmable inference
© 2018 Copyright held by the owner/author(s). We introduce inference metaprogramming for probabilistic programming languages, including new language constructs, a formalism, and the first demonstration of effectiveness in practice. Instead of relying on rigid black-box inference algorithms hard-code...
Main Authors: | Mansinghka, Vikash K., Schaechtle, Ulrich, Handa, Shivam, Radul, Alexey, Chen, Yutian, Rinard, Martin |
---|---|
Other Authors: | MIT-IBM Watson AI Lab |
Format: | Article |
Language: | English |
Published: |
ACM
2021
|
Online Access: | https://hdl.handle.net/1721.1/136984 |
Similar Items
-
Probabilistic Programming with Programmable Variational Inference
by: Becker, McCoy R., et al.
Published: (2024) -
SPPL: probabilistic programming with fast exact symbolic inference
by: Saad, Feras A, et al.
Published: (2022) -
Bayesian synthesis of probabilistic programs for automatic data modeling
by: Saad, Feras A, et al.
Published: (2021) -
Gen: A General-Purpose Probabilistic Programming System with Programmable Inference
by: Cusumano-Towner, Marco F., et al.
Published: (2018) -
Probabilistic Programming with Stochastic Probabilities
by: Lew, Alexander K., et al.
Published: (2023)