NeurIPS 2020

Learning Loss for Test-Time Augmentation

Meta Review

The work proposes a learned loss function for test-time augmentation, with sufficient baseline improvements that all reviewers after discussion found sufficiently convincing. Adding some of the clarifications in the rebuttal (e.g., loss function), and additional experiments, as revisions to the paper would significantly improve the work.