The Influence of Dropout on Membership Inference in Differentially Private Models
Authors: Erick Galinkin | Published: 2021-03-16
Quantification of Uncertainty
Higher-Order Certification for Randomized Smoothing
Authors: Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel | Published: 2020-10-13
Stochastic Linear Bandits Robust to Adversarial Attacks
Authors: Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett | Published: 2020-07-07 | Updated: 2020-10-27
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification
Authors: Sina Däubener, Lea Schönherr, Asja Fischer, Dorothea Kolossa | Published: 2020-05-24 | Updated: 2020-08-02
Confident Learning: Estimating Uncertainty in Dataset Labels
Authors: Curtis G. Northcutt, Lu Jiang, Isaac L. Chuang | Published: 2019-10-31 | Updated: 2022-08-22
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Authors: Eyke Hüllermeier, Willem Waegeman | Published: 2019-10-21 | Updated: 2020-09-16
Can You Trust Your Model’s Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Authors: Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek | Published: 2019-06-06 | Updated: 2019-12-17
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex
Authors: Yufei Cui, Wuguannan Yao, Qiao Li, Antoni B. Chan, Chun Jason Xue | Published: 2019-05-29 | Updated: 2019-09-26
A Marauder’s Map of Security and Privacy in Machine Learning
Authors: Nicolas Papernot | Published: 2018-11-03
Evidential Deep Learning to Quantify Classification Uncertainty
Authors: Murat Sensoy, Lance Kaplan, Melih Kandemir | Published: 2018-06-05 | Updated: 2018-10-31