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A Comparison of Uncertainty Estimation Approaches in Deep Learning
  Components for Autonomous Vehicle Applications

A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications

26 June 2020
F. Arnez
H. Espinoza
A. Radermacher
Franccois Terrier
    UQCV
ArXivPDFHTML

Papers citing "A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications"

8 / 8 papers shown
Title
Deep Modeling of Non-Gaussian Aleatoric Uncertainty
Deep Modeling of Non-Gaussian Aleatoric Uncertainty
Aastha Acharya
Caleb Lee
Marissa DÁlonzo
Jared Shamwell
Nisar R. Ahmed
Rebecca L. Russell
BDL
41
0
0
30 May 2024
Discretization-Induced Dirichlet Posterior for Robust Uncertainty
  Quantification on Regression
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression
Xuanlong Yu
Gianni Franchi
Jindong Gu
Emanuel Aldea
UQCV
11
4
0
17 Aug 2023
Success of Uncertainty-Aware Deep Models Depends on Data Manifold
  Geometry
Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry
M. Penrod
Harrison Termotto
Varshini Reddy
Jiayu Yao
Finale Doshi-Velez
Weiwei Pan
AAML
OOD
35
1
0
02 Aug 2022
Architectural patterns for handling runtime uncertainty of data-driven
  models in safety-critical perception
Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception
Janek Groß
R. Adler
Michael Kläs
Jan Reich
Lisa Jöckel
Roman Gansch
AI4CE
8
5
0
14 Jun 2022
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty
  Estimates for AI Models
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models
Pascal Gerber
Lisa Jöckel
Michael Kläs
17
4
0
10 Jan 2022
Improving Robustness of Deep Neural Networks for Aerial Navigation by
  Incorporating Input Uncertainty
Improving Robustness of Deep Neural Networks for Aerial Navigation by Incorporating Input Uncertainty
F. Arnez
H. Espinoza
A. Radermacher
F. Terrier
UQCV
19
7
0
26 Oct 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
261
9,136
0
06 Jun 2015
1