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Neural Estimation of Summary Statistics for Simulation-Based Inference with Non-Asymptotic Guarantees
Simulation-based inference (SBI) enables Bayesian inference when a simulator is available but the likelihood is intractable. Modern SBI methods train neural networks on simulated data to obtain an amortized approximation of the posterior, making inference for new observations fast. A central challen
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