版本更新 · v5arXiv:2502.03477
Partial Markov Categories
Elena Di Lavore, Mario Román, Paweł Sobociński
We introduce partial Markov categories as a synthetic framework for synthetic probabilistic inference, blending the work of Cho and Jacobs, Fritz, and Golubtsov on Markov categories with the work of Cockett and Lack on cartesian restriction categories. We describe observations, Bayes' theorem, normalisation, and both Pearl's and Jeffrey's updates in purely categorical terms.
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math.CT · cs.LO