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AAAI
2008
14 years 16 days ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
NN
2010
Springer
163views Neural Networks» more  NN 2010»
13 years 5 months ago
Approximating the stability region of a neural network with a general distribution of delays
We investigate the linear stability of a neural network with distributed delay, where the neurons are identical. We examine the stability of a symmetrical equilibrium point via th...
R. Jessop, S. A. Campbell
ICML
2005
IEEE
14 years 11 months ago
Compact approximations to Bayesian predictive distributions
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
Edward Snelson, Zoubin Ghahramani
PG
2000
IEEE
14 years 2 months ago
Interpolating and Approximating Moving Frames Using B-splines
The representation of moving geometry entities is an important issue in the fields of CAD/CAM and robotics motion design. We present a method to interpolate the moving frame homog...
Lizhuang Ma, Tony K. Y. Chan, Zhongding Jiang
ADCM
2008
187views more  ADCM 2008»
13 years 10 months ago
Approximation on the sphere using radial basis functions plus polynomials
In this paper we analyse a hybrid approximation of functions on the sphere S2 R3 by radial basis functions combined with polynomials, with the radial basis functions assumed to be...
Ian H. Sloan, Alvise Sommariva