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» Neural Networks: A Replacement for Gaussian Processes
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NIPS
1997
13 years 10 months ago
Nonlinear Markov Networks for Continuous Variables
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Reimar Hofmann, Volker Tresp
JOCN
2011
66views more  JOCN 2011»
13 years 3 months ago
The Packet Switching Brain
■ The computer metaphor has served brain science well as a tool for comprehending neural systems. Nevertheless, we propose here that this metaphor be replaced or supplemented by...
Daniel J. Graham, Daniel N. Rockmore
ICASSP
2008
IEEE
14 years 3 months ago
Robust kernel density estimation
In this paper, we propose a method for robust kernel density estimation. We interpret a KDE with Gaussian kernel as the inner product between a mapped test point and the centroid ...
JooSeuk Kim, Clayton Scott
MEDINFO
2007
132views Healthcare» more  MEDINFO 2007»
13 years 10 months ago
Comparing Decision Support Methodologies for Identifying Asthma Exacerbations
Objective: To apply and compare common machine learning techniques with an expert-built Bayesian Network to determine eligibility for asthma guidelines in pediatric emergency depa...
Judith W. Dexheimer, Laura E. Brown, Jeffrey Leego...
IJCNN
2008
IEEE
14 years 3 months ago
Stable reciprocal image associations in cognitive systems
—Sensory inputs such as visual images or audio spectrograms can act as symbols in a new cognitive model. The stability of direct image association operators allows the discrete b...
Douglas S. Greer