DR-ABC: Approximate Bayesian computation with kernel-based distribution regression
Performing exact posterior inference in complex generative models is often difficult or impossible due to an expensive to evaluate or intractable likelihood function. Approximate Bayesian computation (ABC) is an inference framework that constructs an approximation to the true likelihood based on the...
| Egile Nagusiak: | , , |
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| Formatua: | Conference item |
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Journal of Machine Learning Research
2016
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