Inference and Learning in Hybrid Bayesian Networks
نویسنده
چکیده
We survey the literature on methods for inference and learning in Bayesian Networks composed of discrete and continuous nodes, in which the continuous nodes have a multivariate Gaussian distribution, whose mean and variance depends on the values of the discrete nodes. We also brie y consider hybrid Dynamic Bayesian Networks, an extension of switching Kalman lters. This report is meant to summarize what is known at a su cient level of detail to enable someone to implement the algorithms, but without dwelling on formalities.1
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