A Survey on Uncertainty Quantification Methods for Deep Learning

26 February 2023

Papers citing "A Survey on Uncertainty Quantification Methods for Deep Learning"

8 / 8 papers shown

Title
Enhanced Detection Classification via Clustering SVM for Various Robot Collaboration Task Rui Liu Xuanzhen Xu Yuwei Shen Armando Zhu Chang Yu Tianjian Chen Ye Zhang 62 34 0 05 May 2024
NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and Denoising Tianchen Deng Yanbo Wang Hongle Xie Hesheng Wang Jingchuan Wang Danwei W. Wang Weidong Chen 3DV 35 22 0 29 Mar 2024
Out-of-Distribution Detection and Selective Generation for Conditional Language Models Jie Jessie Ren Jiaming Luo Yao-Min Zhao Kundan Krishna Mohammad Saleh Balaji Lakshminarayanan Peter J. Liu OODD 64 92 0 30 Sep 2022
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs Philipp Oberdiek G. Fink Matthias Rottmann OODD 21 14 0 31 Jan 2022
Reducing conversational agents' overconfidence through linguistic calibration Sabrina J. Mielke Arthur Szlam Emily Dinan Y-Lan Boureau 197 152 0 30 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 197 2,254 0 18 Oct 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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015