From: NeurIPS.cc/2021/Workshop/DistShift/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: This paper proposes Mixup in input space (off-manifold) and enforces uncertainty on these images yields better accuracy and calibration on corrupted datasets than previous methods. Experiments are quite extensive. In the abstract authors claim good OOD detection, although it does lack behind vanilla ensembles by quite a bit. The high-level idea is not novel but rather quite related to MixUp. What are the concrete details that make it work (slightly) better than MixUp. The paper would hence strongly benefit from a more detailed discussion regarding the difference to MixUp beyond numbers.