Improving Out-of-Distribution Detection via Epistemic Uncertainty
Adversarial Training

Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training

5 September 2022

Luke E. Richards

Papers citing "Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training"

15 / 15 papers shown

Title
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks A. Nguyen Fred Lu Gary Lopez Munoz Edward Raff Charles K. Nicholas James Holt UQCV 46 22 0 18 Feb 2022
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 250 1,911 0 12 Nov 2020
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 97 627 0 05 Dec 2019
On Evaluating Adversarial Robustness Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow Aleksander Madry Alexey Kurakin ELM AAML 79 900 0 18 Feb 2019
On instabilities of deep learning in image reconstruction - Does AI come at a cost? Vegard Antun F. Renna C. Poon Ben Adcock A. Hansen 48 601 0 14 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 82 806 0 07 Feb 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 143 557 0 13 Dec 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 93 1,776 0 30 May 2018
Curriculum Adversarial Training Qi-Zhi Cai Min Du Chang-rui Liu D. Song AAML 66 161 0 13 May 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 240 8,856 0 25 Aug 2017
A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets P. Chrabaszcz I. Loshchilov Frank Hutter SSeg OOD 125 644 0 27 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 263 12,029 0 19 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 326 4,700 0 15 Mar 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 517 5,885 0 08 Jul 2016
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 233 14,893 1 21 Dec 2013