Conference item : Presentation
LF-PPL: A low-level first order probabilistic programming language for non-differentiable models
- Abstract:
-
We develop a new Low-level, First-order Probabilistic Programming Language (LF-PPL) suited for models containing a mix of continuous, discrete, and/or piecewise-continuous variables. The key success of this language and its compilation scheme is in its ability to automatically distinguish parameters the density function is discontinuous with respect to, while further providing runtime checks for boundary crossings. This enables the introduction of new inference engines that are able to exploi...
Expand abstract
- Publication status:
- Published
- Peer review status:
- Reviewed (other)
Actions
Authors
Bibliographic Details
- Publisher:
- ML Research Press
- Journal:
- Proceedings of Machine Learning Research More from this journal
- Volume:
- 89
- Pages:
- 148-157
- Publication date:
- 2019-04-16
- Event title:
- 22nd International Conference on Artificial Intelligence and Statistics
- Event location:
- Naha, Okinawa, Japan
- Event website:
- http://proceedings.mlr.press/v89/
- Event start date:
- 2019-04-16
- Event end date:
- 2019-04-18
- ISSN:
-
2640-3498
Item Description
- Language:
-
English
- Keywords:
- Subtype:
-
Presentation
- Pubs id:
-
1091046
- Local pid:
-
pubs:1091046
- Deposit date:
-
2020-09-03
Terms of use
- Copyright holder:
- Zhou et al.
- Copyright date:
- 2019
- Rights statement:
- Copyright 2019 by the author(s).
Metrics
If you are the owner of this record, you can report an update to it here: Report update to this record