# Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage

@inproceedings{Dalmasso2021LikelihoodFreeFI, title={Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage}, author={Niccol{\`o} Dalmasso and Luca Masserano and Dave Zhao and Rafael Izbicki and Ann B. Lee}, year={2021} }

Many areas of science make extensive use of computer simulators that implicitly encode likelihood functions of complex systems. Classical statistical methods are poorly suited for these so-called likelihood-free inference (LFI) settings, particularly outside asymptotic and low-dimensional regimes. Although new machine learning methods, such as normalizing ﬂows, have revolutionized the sample eﬃciency and capacity of LFI methods, it remains an open question whether they produce conﬁdence sets…

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