Disrupting Deep Uncertainty Estimation Without Harming Accuracy

26 October 2021

Papers citing "Disrupting Deep Uncertainty Estimation Without Harming Accuracy"

12 / 12 papers shown

Title
Uncertainty Quantification for Machine Learning in Healthcare: A Survey L. J. L. Lopez Shaza Elsharief Dhiyaa Al Jorf Firas Darwish Congbo Ma Farah E. Shamout 104 0 0 04 May 2025
On the Robustness of Adversarial Training Against Uncertainty Attacks Emanuele Ledda Giovanni Scodeller Daniele Angioni Giorgio Piras Antonio Emanuele Cinà Giorgio Fumera Battista Biggio Fabio Roli AAML 30 1 0 29 Oct 2024
Overcoming Common Flaws in the Evaluation of Selective Classification Systems Jeremias Traub Till J. Bungert Carsten T. Lüth Michael Baumgartner Klaus H. Maier-Hein Lena Maier-Hein Paul F. Jaeger 36 3 0 01 Jul 2024
Towards Certification of Uncertainty Calibration under Adversarial Attacks Cornelius Emde Francesco Pinto Thomas Lukasiewicz Philip H. S. Torr Adel Bibi AAML 42 0 0 22 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks Yunzhen Feng Tim G. J. Rudner Nikolaos Tsilivis Julia Kempe AAML BDL 43 1 0 27 Apr 2024
Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting P. Proskura Alexey Zaytsev 26 0 0 22 Feb 2024
Calibration Attacks: A Comprehensive Study of Adversarial Attacks on Model Confidence Stephen Obadinma Xiaodan Zhu Hongyu Guo AAML 14 1 0 05 Jan 2024
Calibrating Multimodal Learning Huanrong Zhang Changqing Zhang Bing Wu H. Fu Joey Tianyi Zhou Q. Hu 59 16 0 02 Jun 2023
On Attacking Out-Domain Uncertainty Estimation in Deep Neural Networks Huimin Zeng Zhenrui Yue Yang Zhang Ziyi Kou Lanyu Shang Dong Wang OOD AAML 33 7 0 03 Oct 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,660 0 05 Dec 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,835 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015