Towards Dependability Metrics for Neural Networks

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Towards Dependability Metrics for Neural Networks

6 June 2018

Chih-Hong Cheng

Georg Nührenberg

Chung-Hao Huang

Hirotoshi Yasuoka

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Papers citing "Towards Dependability Metrics for Neural Networks"

9 / 9 papers shown

Title
Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems Chih-Hong Cheng Chung-Hao Huang Hirotoshi Yasuoka 40 41 0 11 May 2018
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 125 1,504 0 02 Nov 2017
Neural Networks for Safety-Critical Applications - Challenges, Experiments and Perspectives Chih-Hong Cheng Frederik Diehl Yassine Hamza Gereon Hinz Georg Nührenberg Markus Rickert Harald Ruess Michael Truong-Le AAML 43 34 0 04 Sep 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 102 1,371 0 18 May 2017
Maximum Resilience of Artificial Neural Networks Chih-Hong Cheng Georg Nührenberg Harald Ruess AAML 111 284 0 28 Apr 2017
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 151 4,903 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,107 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 277 14,961 1 21 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,893 0 12 Nov 2013