Automatic inference for higher-order probabilistic programs
Probabilistic models used in quantitative sciences have historically co-evolved with methods for performing inference: specific modeling assumptions are made not because they are appropriate to the application domain, but because they are required to leverage existing software packages or inference...
Main Author: | Paige, Timothy Brooks |
---|---|
Other Authors: | Wood, Frank |
Published: |
University of Oxford
2016
|
Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730289 |
Similar Items
-
Probabilistic programming with programmable inference
by: Mansinghka, Vikash K., et al.
Published: (2021) -
Inference processes for probabilistic first order languages
by: Rad, Soroush Rafiee
Published: (2009) -
Computability, inference and modeling in probabilistic programming
by: Roy, Daniel Murphy
Published: (2011) -
Automatic segmentation of coronary angiograms based on fuzzy inferring and probabilistic tracking
by: Shoujun Zhou, et al.
Published: (2010-08-01) -
Higher-order inference for vision problems
by: Russell, Chris
Published: (2012)