Sciweavers

4981 search results - page 32 / 997
» Dependent Gaussian Processes
Sort
View
ICASSP
2011
IEEE
14 years 1 months ago
Nonstationary and temporally correlated source separation using Gaussian process
Blind source separation (BSS) is a process to reconstruct source signals from the mixed signals. The standard BSS methods assume a fixed set of stationary source signals with the ...
Hsin-Lung Hsieh, Jen-Tzung Chien
CVPR
2006
IEEE
15 years 11 months ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua
ICML
2007
IEEE
15 years 10 months ago
Most likely heteroscedastic Gaussian process regression
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
Kristian Kersting, Christian Plagemann, Patrick Pf...
ICML
2007
IEEE
15 years 10 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
ICML
2005
IEEE
15 years 10 months ago
Near-optimal sensor placements in Gaussian processes
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
Carlos Guestrin, Andreas Krause, Ajit Paul Singh