571 citations · 624 across the 2 of their papers we have counts for
3 papers
stat.ML2019★ 571 cited
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
Dan Hendrycks, Norman Mu, Ekin D. Cubuk +3
Modern deep neural networks can achieve high accuracy when the training distribution and test distribution are identically distributed, but this assumption is frequently violated i…
cs.CV2019★ 53 cited
MNIST-C: A Robustness Benchmark for Computer Vision
Norman Mu, Justin Gilmer
We introduce the MNIST-C dataset, a comprehensive suite of 15 corruptions applied to the MNIST test set, for benchmarking out-of-distribution robustness in computer vision. Through…
cs.LG2018
Parameter Re-Initialization through Cyclical Batch Size Schedules
Norman Mu, Zhewei Yao, Amir Gholami +2
Optimal parameter initialization remains a crucial problem for neural network training. A poor weight initialization may take longer to train and/or converge to sub-optimal solutio…