Xiaoyin Bai

Improving Robustness of Post-hoc Calibration Against Common Corruptions By Learnable Augmentation

Various research has addressed the overconfidence problem, and we focus on improving the robustness of post-hoc calibration (e.g., temperature scaling, TS) when the test set shifts from the training set by image corruption. TS is greatly affected by the validation set, which previous work has propos…