A Critical Evaluation of Open-World Machine Learning

A Critical Evaluation of Open-World Machine Learning

8 July 2020

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Papers citing "A Critical Evaluation of Open-World Machine Learning"

13 / 13 papers shown

Title
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors Peter Lorenz Mario Fernandez Jens Müller Ullrich Kothe AAML 146 1 0 21 Jun 2024
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt Basel Alomair OODD 212 1,482 0 16 Jul 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 183 1,483 0 11 Dec 2018
Recent Advances in Open Set Recognition: A Survey Chuanxing Geng Sheng-Jun Huang Songcan Chen BDL ObjD 141 771 0 21 Nov 2018
Reducing Network Agnostophobia A. Dhamija Manuel Günther Terrance E. Boult AAML UQCV 73 302 0 09 Nov 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 187 2,060 0 10 Jul 2018
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 310 12,117 0 19 Jun 2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 171 2,080 0 08 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 48 1,208 0 25 May 2017
Robust, Deep and Inductive Anomaly Detection Raghavendra Chalapathy A. Menon Sanjay Chawla 63 161 0 22 Apr 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 166 3,468 0 07 Oct 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 349 7,995 0 23 May 2016
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