Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations

TY - JOUR

T1 - Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations

AU - Schölkopf, B.

AU - Muandet, K.

AU - Fukumizu, K.

AU - Harmeling, S.

AU - Peters, Jonas Martin

PY - 2015/7/26

Y1 - 2015/7/26

N2 - 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.

AB - 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.

U2 - 10.1007/s11222-015-9558-5

DO - 10.1007/s11222-015-9558-5

M3 - Journal article

SN - 0960-3174

VL - 25

SP - 755

EP - 766

JO - Statistics and Computing

JF - Statistics and Computing

IS - 4

ER -