2022
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification
ICML 2022spotlight
The reliability of neural networks is essential for their use in safety-critical applications. Existing approaches generally aim at improving the robustness of neural networks to either real-world distribution shifts (e.g., common corruptions and perturbations, spatial transformations, and natural a…