Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference

3 Mar 2019Kelvin HsuFabio Ramos

In likelihood-free settings where likelihood evaluations are intractable, approximate Bayesian computation (ABC) addresses the formidable inference task to discover plausible parameters of simulation programs that explain the observations. However, they demand large quantities of simulation calls... (read more)

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