SPIN improves posterior inference under model misspecification in SBI by learning parameter-relevant information-preserving domain transfers from unpaired unlabeled real-world data.
Detecting model misspecification in amortized bayesian inference with neural networks
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Information-Preserving Domain Transfer with Unlabeled Data in Misspecified Simulation-Based Inference
SPIN improves posterior inference under model misspecification in SBI by learning parameter-relevant information-preserving domain transfers from unpaired unlabeled real-world data.