Estimating the Brittleness of AI: Safety Integrity Levels and the Need for Testing Out-Of-Distribution Performance

2 September 2020

Papers citing "Estimating the Brittleness of AI: Safety Integrity Levels and the Need for Testing Out-Of-Distribution Performance"

5 / 5 papers shown

Title
Improved OOD Generalization via Adversarial Training and Pre-training Mingyang Yi Lu Hou Jiacheng Sun Lifeng Shang Xin Jiang Qun Liu Zhi-Ming Ma VLM 31 83 0 24 May 2021
Fixing the train-test resolution discrepancy: FixEfficientNet Hugo Touvron Andrea Vedaldi Matthijs Douze Hervé Jégou AAML 196 110 0 18 Mar 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 28 36 0 26 Dec 2019
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 69 264 0 30 Nov 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,892 0 15 Sep 2016