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» Modelling Smooth Paths Using Gaussian Processes
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CORR
2010
Springer
175views Education» more  CORR 2010»
13 years 5 months ago
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
Ryan Prescott Adams, George E. Dahl, Iain Murray
ICASSP
2008
IEEE
14 years 6 days ago
Multiple fundamental frequency estimation using Gaussian smoothness
A multiple fundamental frequency estimator is presented in this work. At each time frame, a set of fundamental frequencies is found in a frame by frame analysis taking into accoun...
Antonio Pertusa, José Manuel Iñesta ...
ISCAS
2003
IEEE
107views Hardware» more  ISCAS 2003»
13 years 11 months ago
On chip Gaussian processing for high resolution CMOS image sensors
Spatial image processing chips, known as silicon retinas, are based on the architecture of vertebrate retina and can be mathematically represented as the Laplacian of Gaussian (LO...
Sri Vinayagamoorthy, Richard Hornsey
NIPS
2007
13 years 7 months ago
Robust Regression with Twinned Gaussian Processes
We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...
Andrew Naish-Guzman, Sean B. Holden
DSMML
2004
Springer
13 years 11 months ago
Understanding Gaussian Process Regression Using the Equivalent Kernel
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show how to approximat...
Peter Sollich, Christopher K. I. Williams