Be Bayesian by Attachments to Catch More Uncertainty

19 October 2023

Papers citing "Be Bayesian by Attachments to Catch More Uncertainty"

6 / 6 papers shown

Title
Extremely Simple Activation Shaping for Out-of-Distribution Detection Andrija Djurisic Nebojsa Bozanic Arjun Ashok Rosanne Liu OODD 152 146 0 20 Sep 2022
Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei Renchunzi Xie Hao-Ran Cheng Lei Feng Bo An Yixuan Li OODD 163 258 0 19 May 2022
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models Lily H. Zhang Mark Goldstein Rajesh Ranganath OODD 135 103 0 14 Jul 2021
A Bayesian Federated Learning Framework with Online Laplace Approximation Liang Liu Xi Jiang Feng Zheng Hong Chen Guo-Jun Qi Heng-Chiao Huang Ling Shao FedML 38 53 0 03 Feb 2021
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong Jimeng Sun Chao Zhang UQCV 42 101 0 24 Aug 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016