Computing functions of random variables via reproducing kernel Hilbert space representations
OPEN ACCESS
Loading...
Author / Producer
Date
2015-07
Publication Type
Journal Article
ETH Bibliography
yes
Citations
Altmetric
OPEN ACCESS
Data
Rights / License
Abstract
We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations which can be applied to points drawn from the respective distributions. We refer to our approach as kernel probabilistic programming. We illustrate it on synthetic data and show how it can be used for nonparametric structural equation models, with an application to causal inference.
Permanent link
Publication status
published
External links
Editor
Book title
Journal / series
Volume
25 (4)
Pages / Article No.
755 - 766
Publisher
Springer
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Kernel methods; Probabilistic programming; Causal inference