Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations

6 December 2019

Krishnamurthy Dvijotham

Papers citing "Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations"

20 / 20 papers shown

Title
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors Shuangpeng Han Mengmi Zhang 116 0 0 03 Oct 2024
On Counterfactual Data Augmentation Under Confounding Abbavaram Gowtham Reddy Saketh Bachu Saloni Dash Charchit Sharma Amit Sharma V. Balasubramanian CML BDL 33 0 0 29 May 2023
Assessing Neural Network Robustness via Adversarial Pivotal Tuning Peter Ebert Christensen Vésteinn Snaebjarnarson Andrea Dittadi Serge J. Belongie Sagie Benaim AAML 23 1 0 17 Nov 2022
Discovering Bugs in Vision Models using Off-the-shelf Image Generation and Captioning Olivia Wiles Isabela Albuquerque Sven Gowal VLM 30 47 0 18 Aug 2022
Latent Space Smoothing for Individually Fair Representations Momchil Peychev Anian Ruoss Mislav Balunović Maximilian Baader Martin Vechev FaML 36 19 0 26 Nov 2021
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang Chaowei Xiao Jean Kossaifi Zhiding Yu Anima Anandkumar Zhangyang Wang 19 106 0 26 Oct 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 22 293 0 18 Oct 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Exposing Previously Undetectable Faults in Deep Neural Networks Isaac Dunn Hadrien Pouget Daniel Kroening T. Melham AAML 23 28 0 01 Jun 2021
Ensembling with Deep Generative Views Lucy Chai Jun-Yan Zhu Eli Shechtman Phillip Isola Richard Y. Zhang GAN 27 70 0 29 Apr 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 27 268 0 02 Mar 2021
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks L. N. Darlow Stanisław Jastrzębski Amos Storkey 46 24 0 19 Nov 2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations Chongli Qin Yan Wu Jost Tobias Springenberg Andrew Brock Jeff Donahue Timothy Lillicrap Pushmeet Kohli GAN 22 28 0 28 Oct 2020
On the Transfer of Disentangled Representations in Realistic Settings Andrea Dittadi Frederik Trauble Francesco Locatello M. Wuthrich Vaibhav Agrawal Ole Winther Stefan Bauer Bernhard Schölkopf OOD 30 80 0 27 Oct 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 279 10,348 0 12 Dec 2018
Constructing Unrestricted Adversarial Examples with Generative Models Yang Song Rui Shu Nate Kushman Stefano Ermon GAN AAML 185 302 0 21 May 2018
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016
Conditional Image Synthesis With Auxiliary Classifier GANs Augustus Odena C. Olah Jonathon Shlens GAN 238 3,190 0 30 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 284 5,835 0 08 Jul 2016