Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors Qixun Wang 1* Yifei Wang

This provides us with clues that adversarial perturbations with universal (low dimensional) structures can enhance the robustness against large data distribution shifts that are common in OOD scenarios.