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UAI
2001
14 years 6 days ago
Exact Inference in Networks with Discrete Children of Continuous Parents
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
Uri Lerner, Eran Segal, Daphne Koller
IJAR
2006
98views more  IJAR 2006»
13 years 10 months ago
Inference in hybrid Bayesian networks with mixtures of truncated exponentials
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function can be approximated...
Barry R. Cobb, Prakash P. Shenoy
UAI
1998
14 years 5 days ago
Large Deviation Methods for Approximate Probabilistic Inference
We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
Michael J. Kearns, Lawrence K. Saul
ICCV
2001
IEEE
15 years 23 days ago
Continuous Global Evidence-Based Bayesian Modality Fusion for Simultaneous Tracking of Multiple Objects
Robust, real-time tracking of objects from visual data requires probabilistic fusion of multiple visual cues. Previous approaches have either been ad hoc or relied on a Bayesian n...
Jamie Sherrah, Shaogang Gong
ISBI
2011
IEEE
13 years 2 months ago
Discriminative persistent homology of brain networks
It is known that the brain network has small-world and scalefree topology, but the network structures drastically change depending on how to threshold a connectivity matrix. The e...
Hyekyoung Lee, Moo K. Chung, Hyejin Kang, Bung-Nyu...