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+ <h2><a name="models">Supported probabilistic models</h2> 
+<p> 
+It is trivial to implement all of
+the following probabilistic models using the toolbox.
+<ul> 
+<li>Static
+<ul> 
+<li> Linear regression, logistic regression, hierarchical mixtures of experts
+ 
+<li> Naive Bayes classifiers, mixtures of Gaussians,
+sigmoid belief nets
+ 
+<li> Factor analysis, probabilistic
+PCA, probabilistic ICA, mixtures of these models
+ 
+</ul> 
+ 
+<li>Dynamic
+<ul> 
+ 
+<li> HMMs, Factorial HMMs, coupled HMMs, input-output HMMs, DBNs
+ 
+<li> Kalman filters, ARMAX models, switching Kalman filters,
+tree-structured Kalman filters, multiscale AR models
+ 
+</ul> 
+ 
+<li> Many other combinations, for which there are (as yet) no names!
+ 
+</ul> 
+ 
+ 
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