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AAAI
2008
15 years 8 months 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»
15 years 1 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
16 years 7 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
15 years 11 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»
15 years 6 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