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Uncertainty Quantification via Stable Distribution Propagation

Uncertainty Quantification via Stable Distribution Propagation

13 February 2024
Felix Petersen
Aashwin Mishra
Hilde Kuehne
Christian Borgelt
Oliver Deussen
Mikhail Yurochkin
    UQCV
ArXivPDFHTML

Papers citing "Uncertainty Quantification via Stable Distribution Propagation"

5 / 5 papers shown
Title
Streamlining Prediction in Bayesian Deep Learning
Streamlining Prediction in Bayesian Deep Learning
Rui Li
Marcus Klasson
Arno Solin
Martin Trapp
UQCV
BDL
91
2
0
27 Nov 2024
Generalizing Stochastic Smoothing for Differentiation and Gradient
  Estimation
Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation
Felix Petersen
Christian Borgelt
Aashwin Mishra
Stefano Ermon
31
1
0
10 Oct 2024
Differentiable Collision Detection: a Randomized Smoothing Approach
Differentiable Collision Detection: a Randomized Smoothing Approach
Louis Montaut
Quentin Le Lidec
Antoine Bambade
Vladimir Petrik
Josef Sivic
Justin Carpentier
38
28
0
19 Sep 2022
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
268
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
247
9,134
0
06 Jun 2015
1