From: NeurIPS.cc/2022/Workshop/DistShift/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: An empirical analysis of how robust classifiers are to ImageNet-C blurs versus more realistic optical blur kernels is both interesting and valuable to the community in order to tease out the relationship between different types of robustness and best practices for benchmarking robustness to distribution shift. I encourage the authors to address the feedback of Reviewer YvT2 - i.e. improving the presentation of the empirical results with scatterplots and providing more optics background where necessary.