K2-ABC: Approximate Bayesian computation with kernel embeddings
Complicated generative models often result in a situation where computing the likelihood of observed data is intractable, while simulating from the conditional density given a parameter value is relatively easy. Approximate Bayesian Computation (ABC) is a paradigm that enables simulation-based poste...
| मुख्य लेखकों: | , , |
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| स्वरूप: | Conference item |
| प्रकाशित: |
Proceedings of Machine Learning Research
2016
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