Model misspecification is one of the trickier challenges in SBI: what happens when your simulator doesn’t capture the observed data?
I wrote an overview of the problem and methods to detect and handle it, now out in the ICLR 2026 blog post track: iclr-blogposts.github.io/2026/blog/20...
iclr-blogposts.github.io
Model Misspecification in Simulation-Based Inference - Recent Advances and Open Challenges | ICLR Blogposts 2026
Model misspecification is a critical challenge in simulation-based inference (SBI), particularly in neural SBI methods that use simulated data to train flexible neural density estimators. These method...
