Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification

4 December 2020

Papers citing "Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification"

8 / 8 papers shown

Title
Benchmarking Scalable Epistemic Uncertainty Quantification in Organ Segmentation Jadie Adams Shireen Elhabian UQCV 18 5 0 15 Aug 2023
Instance-Aware Observer Network for Out-of-Distribution Object Segmentation Victor Besnier Andrei Bursuc David Picard Alexandre Briot 39 1 0 18 Jul 2022
FIFO: Learning Fog-invariant Features for Foggy Scene Segmentation Sohyun Lee Taeyoung Son Suha Kwak 45 72 0 04 Apr 2022
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks Gianni Franchi Xuanlong Yu Andrei Bursuc Ángel Tena Rémi Kazmierczak Séverine Dubuisson Emanuel Aldea David Filliat UQCV 23 28 0 02 Mar 2022
Neural Bootstrapper Minsuk Shin Hyungjoon Cho Hyun-Seok Min Sungbin Lim UQCV BDL 20 7 0 02 Oct 2020
On a Sparse Shortcut Topology of Artificial Neural Networks Fenglei Fan Dayang Wang Hengtao Guo Qikui Zhu Pingkun Yan Ge Wang Hengyong Yu 38 21 0 22 Nov 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 273 5,660 0 05 Dec 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