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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > UQ perspectives on approximate Bayesian computation (ABC)
UQ perspectives on approximate Bayesian computation (ABC)Add to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact INI IT. UNQW01 - Key UQ methodologies and motivating applications Approximate Bayesian computation (ABC) methods are widely used in some scientific disciplines for fitting stochastic simulators to data. They are primarily used in situations where the likelihood function of the simulator is unknown, but where it is possible to easily sample from the simulator. Methodological development of ABC methods has primarily focused on computational efficiency and tractability, rather than on careful uncertainty modelling. In this talk I'll briefly introduce ABC and its various extensions, and then interpret it from a UQ perspective and suggest how it may best be modified. This talk is part of the Isaac Newton Institute Seminar Series series. This talk is included in these lists:
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