Active diffusion-based methods can discover correct parameter regions even when initial training bounds exclude true parameters by iteratively detecting and correcting model misspecification through posterior uncertainty

By iteratively detecting and correcting model misspecification through posterior uncertainty, the method discovers and learns the correct region of parameter space, even when initial training bounds exclude the true parameters.

http://arxiv.org/abs/2608.27080v1