Gradient density estimation in arbitrary finite dimensions using the method of stationary phase

11/13/2012
by   Karthik S. Gurumoorthy, et al.
0

We prove that the density function of the gradient of a sufficiently smooth function S : Ω⊂R^d →R, obtained via a random variable transformation of a uniformly distributed random variable, is increasingly closely approximated by the normalized power spectrum of ϕ=(iS/τ) as the free parameter τ→ 0. The result is shown using the stationary phase approximation and standard integration techniques and requires proper ordering of limits. We highlight a relationship with the well-known characteristic function approach to density estimation, and detail why our result is distinct from this approach.

READ FULL TEXT

page 19

page 20

page 21

page 22

page 23

page 24

research
08/08/2011

An application of the stationary phase method for estimating probability densities of function derivatives

We prove a novel result wherein the density function of the gradients---...
research
04/19/2011

Distance Transform Gradient Density Estimation using the Stationary Phase Approximation

The complex wave representation (CWR) converts unsigned 2D distance tran...
research
03/01/2019

Approximation by finite mixtures of continuous density functions that vanish at infinity

Given sufficiently many components, it is often cited that finite mixtur...
research
09/09/2022

Non-ergodic statistics and spectral density estimation for stationary real harmonizable symmetric α-stable processes

We consider stationary real harmonizable symmetric α-stable processes X=...
research
05/11/2023

Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable

The deep generative model yields an implicit estimator for the unknown d...
research
01/16/2013

Utilities as Random Variables: Density Estimation and Structure Discovery

Decision theory does not traditionally include uncertainty over utility ...
research
06/09/2020

AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation

Entropy is ubiquitous in machine learning, but it is in general intracta...

Please sign up or login with your details

Forgot password? Click here to reset