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    CVPR
    1999
    IEEE
    207views Computer Vision» more  CVPR 1999»
    Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
    14 years 11 months ago
    Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
    Download  www.psi.toronto.edu
    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...
    Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
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    ECCV
    2000
    Springer
    145views Computer Vision» more  ECCV 2000»
    Non-linear Bayesian Image Modelling
    14 years 11 months ago
    Non-linear Bayesian Image Modelling
    Download  johnwinn.org
    In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
    Christopher M. Bishop, John M. Winn
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    UAI
    1996
    146views Artificial Intelligence» more  UAI 1996»
    Context-Specific Independence in Bayesian Networks
    13 years 10 months ago
    Context-Specific Independence in Bayesian Networks
    Download  robotics.stanford.edu
    Bayesiannetworks provide a languagefor qualitatively representing the conditional independence properties of a distribution. This allows a natural and compact representation of th...
    Craig Boutilier, Nir Friedman, Moisés Golds...
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    ACL
    2012
    230views Computational Linguistics» more  ACL 2012»
    Learning to "Read Between the Lines" using Bayesian Logic Programs
    11 years 11 months ago
    Learning to "Read Between the Lines" using Bayesian Logic Programs
    Download  aclweb.org
    Most information extraction (IE) systems identify facts that are explicitly stated in text. However, in natural language, some facts are implicit, and identifying them requires â€...
    Sindhu Raghavan, Raymond J. Mooney, Hyeonseo Ku
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    HYBRID
    2000
    Springer
    191views Control Systems» more  HYBRID 2000»
    A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
    14 years 19 days ago
    A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
    Download  www.ifp.illinois.edu
    Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
    Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
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