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What is Likelihood-Free Parameter Estimation With Neural Bayes Estimators about?

This article discusses the development and application of Neural Bayes estimators, which are neural networks designed to approximate Bayes estimators for likelihood-free parameter estimation. The authors highlight the advantages of these estimators, including their speed and ability to handle replicated data using permutation-invariant neural networks. They provide extensive simulation studies and practical implementation guidance, along with open-source software to facilitate adoption in statistical applic

Author

lijisheng754

Language

EN