233 search results - page 7 / 47 » Probabilistic Modeling for Structural Change Inference |
89
Voted
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
IJAR
2010
14 years 8 months ago
2010
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
IUI
2003
ACM
15 years 2 months ago
2003
ACM
We present a probabilistic model, based on Dynamic Decision Networks, to assess user affect from possible causes of emotional arousal. The model relies on the OCC cognitive theory...
101
Voted
BMCBI
2010
14 years 9 months ago
2010
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
NIPS
2003
14 years 11 months ago
2003
Rao–Blackwellization is an approximation technique for probabilistic inference that flexibly combines exact inference with sampling. It is useful in models where conditioning o...