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Norman Mu
Researcher at Google
Publications - 8
Citations - 1656
Norman Mu is an academic researcher from Google. The author has contributed to research in topics: Robustness (computer science) & Computer science. The author has an hindex of 5, co-authored 7 publications receiving 610 citations. Previous affiliations of Norman Mu include University of California, Berkeley.
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The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
Dan Hendrycks,Steven Basart,Norman Mu,Saurav Kadavath,Frank Wang,Evan Dorundo,Rahul Desai,Tyler Zhu,Samyak Parajuli,Mike Guo,Dawn Song,Jacob Steinhardt,Justin Gilmer +12 more
TL;DR: It is found that using larger models and artificial data augmentations can improve robustness on real-world distribution shifts, contrary to claims in prior work.
Proceedings Article
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
TL;DR: AugMix significantly improves robustness and uncertainty measures on challenging image classification benchmarks, closing the gap between previous methods and the best possible performance in some cases by more than half.
Posted ContentDOI
MNIST-C: A Robustness Benchmark for Computer Vision.
Norman Mu,Justin Gilmer +1 more
TL;DR: This work demonstrates that several previously published adversarial defenses significantly degrade robustness as measured by MNIST-C, a comprehensive suite of 15 corruptions applied to the MNIST test set, and hopes that this benchmark serves as a useful tool for future work in designing systems that are able to learn robust feature representations that capture the underlying semantics of the input.
Posted Content
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
TL;DR: AugMix as discussed by the authors improves the robustness and uncertainty estimates of image classifiers by adding a data processing technique that is simple to implement, adds limited computational overhead, and helps models withstand unforeseen corruptions.
Proceedings Article
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
Dan Hendrycks,Steven Basart,Norman Mu,Saurav Kadavath,Frank Wang,Evan Dorundo,Rahul Desai,Tyler Zhu,Samyak Parajuli,Mike Guo,Dawn Song,Jacob Steinhardt,Justin Gilmer +12 more
TL;DR: In this article, the authors introduce four new real-world distribution shift datasets consisting of changes in image style, image blurriness, geographic location, camera operation, and more.