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128
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IJCAI
2007
15 years 5 months ago
Compiling Bayesian Networks by Symbolic Probability Calculation Based on Zero-Suppressed BDDs
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
Shin-ichi Minato, Ken Satoh, Taisuke Sato
169
Voted
NIPS
2008
15 years 5 months ago
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
Identification and comparison of nonlinear dynamical system models using noisy and sparse experimental data is a vital task in many fields, however current methods are computation...
Ben Calderhead, Mark Girolami, Neil D. Lawrence
132
Voted
NIPS
2004
15 years 5 months ago
Spike Sorting: Bayesian Clustering of Non-Stationary Data
Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
Aharon Bar-Hillel, Adam Spiro, Eran Stark
141
Voted
NIPS
2001
15 years 5 months ago
MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation
Bayesian belief propagation in graphical models has been recently shown to have very close ties to inference methods based in statistical physics. After Yedidia et al. demonstrate...
Anand Rangarajan, Alan L. Yuille
113
Voted
CORR
2010
Springer
80views Education» more  CORR 2010»
15 years 3 months ago
Multi-path Probabilistic Available Bandwidth Estimation through Bayesian Active Learning
Knowing the largest rate at which data can be sent on an end-to-end path such that the egress rate is equal to the ingress rate with high probability can be very practical when ch...
Frederic Thouin, Mark Coates, Michael Rabbat