33 search results - page 5 / 7 » Nonparametric Bayesian Learning of Switching Linear Dynamica... |
110
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MMAS
2011
Springer
14 years 4 months ago
2011
Springer
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
140
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AINA
2008
IEEE
15 years 4 months ago
2008
IEEE
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
CDC
2010
IEEE
14 years 4 months ago
2010
IEEE
Abstract-- This paper focuses on the identification of nonlinear hybrid systems involving unknown nonlinear dynamics. The proposed method extends the framework of [1] by introducin...
CVPR
1999
IEEE
15 years 11 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
106
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AROBOTS
2011
14 years 4 months ago
2011
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...