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Preconditioned Neural Posterior Estimation for Likelihood-free Inference
To overcome this, we propose preconditioned NPE (PNPE) and its sequential version (PSNPE), which uses a short run of ABC to effectively eliminate regions of parameter space that produce large discrepancy between simulations and data and allow the posterior emulator to be more accurately trained.
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference
Simulation-based inference techniques are indispensable for parameter estimation of mechanistic and simulable models with intractable likelihoods.
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