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Robust Bayesian methods using amortized simulation-based inference
Bayesian simulation-based inference (SBI) methods are used in statistical models where simulation is feasible but the likelihood is intractable. Standard SBI methods can perform poorly in cases of model misspecification, and there has been much recent work on modified SBI approaches which are robust
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