Approximate Bayesian computation with path signatures

Simulation models often lack tractable likelihood functions, making likelihood-free inference methods indispensable. Approximate Bayesian computation generates likelihood-free posterior samples by comparing simulated and observed data through some distance measure, but existing approaches are often...

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מידע ביבליוגרפי
Main Authors: Dyer, J, Cannon, P, Schmon, SM
פורמט: Conference item
שפה:English
יצא לאור: Proceedings of Machine Learning Research 2024

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