Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling

2 February 2023

Papers citing "Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling"

7 / 7 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 190 0 0 04 May 2025
Local Flow Matching Generative Models Chen Xu Xiuyuan Cheng Yao Xie 49 1 0 03 Jan 2025
Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models Lucas Berry Axel Brando David Meger 32 6 0 05 Jun 2024
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models Lily H. Zhang Mark Goldstein Rajesh Ranganath OODD 143 103 0 14 Jul 2021
Cubic-Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios TPM 53 57 0 05 Jun 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,695 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015