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<tr><th>Model</th><th>Domain</th><th>Algorithm</th></tr>
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<tr><td rowspan="6">Bayesian Network</td><td>Input/Output</td><td> bif/bifxml/dsl/net formats (read/write)</td></tr>
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<tr><td>Exact Inference with Relevant Reasonning </td><td> Variable Elimination Shafer-Shenoy Inference Lazy Propagation </td></tr>
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<tr><td>Approximated Inference</td><td>Gibbs Sampling, *Loopy Belief Propagation*</td></tr>
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<tr><td>Approximated Inference</td><td>Gibbs Sampling, Loopy Belief Propagation</td></tr>
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<tr><td>Parameter Learning</td><td>Pure maxLikelihood, Laplace, Dirichlet </td></tr>
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<tr><td> Structural Learning</td><td>Local search with Tabu List Greedy Hill Climbing K2 constraints : mandatory/forbidden arcs,etc.</td></tr>
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<tr><td>Miscellenaous </td><td> Exact and <b>approximated</b> distance/divergence between BNs (KL, Bhattacharya, Hellinger) Mutual information, entropy, Simulation (generation of csv files), etc.</td></tr>
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