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==== Filtering ====
The task is to compute, given the model's parameters and a sequence of observations, the distribution over hidden states of the last latent variable at the end of the sequence, i.e. to compute <math>P(x(t)\ |\ y(1),\dots,y(t))</math>.
This problem can be handled efficiently using the [[forward algorithm]]. An example is when the algorithm is applied to a Hidden Markov Network to determine <math>\mathrm{P}\big( h_t \ | v_{1:t} \big)</math>.
==== Smoothing ====
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