Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness

26 June 2019

Papers citing "Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness"

8 / 8 papers shown

Title
Strong inductive biases provably prevent harmless interpolation Michael Aerni Marco Milanta Konstantin Donhauser Fanny Yang 35 9 0 18 Jan 2023
A Simple Strategy to Provable Invariance via Orbit Mapping Kanchana Vaishnavi Gandikota Jonas Geiping Zorah Lähner Adam Czapliñski Michael Moeller AAML 3DPC 18 3 0 24 Sep 2022
Improving the Sample-Complexity of Deep Classification Networks with Invariant Integration M. Rath A. P. Condurache 25 8 0 08 Feb 2022
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 22 531 0 01 Jul 2020
Toward Adversarial Robustness via Semi-supervised Robust Training Yiming Li Baoyuan Wu Yan Feng Yanbo Fan Yong Jiang Zhifeng Li Shutao Xia AAML 87 13 0 16 Mar 2020
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang AAML 48 222 0 25 Feb 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016