MCMC: A demo showing how to use Gibbs sampling for approximate sampling, and how to use sampling methods for approximate decoding/inference.ICM: A demo showing how to use the iteratedĬonditional mode algorithm (and other local search algorithms) for approximate decoding.The second set of demos covers approximate decoding/inference/sampling methods: GraphCuts: An example of a complicated loopy UGM, where the use of sub-moodular potentials (over binary data) allows us to perform exact decoding.Junction: A more complicated loopy UGM, where we take advantage of the low treewidth of the graph structure to perform exact decoding/inference/sampling.Cutset: Two examples of simple loopy UGMs, where we take advantage of the simplified graph structure after conditioning to perform exact decoding/inference/sampling.Condition: A demo that shows how we canĭo conditional decoding/inference/sampling, if we know the values of some. ![]()
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