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Ensemble models outperform single model uncertainties and predictions
  for operator-learning of hypersonic flows

Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows

31 October 2023
Victor J. Leon
Noah Ford
Honest Mrema
Jeffrey Gilbert
Alexander New
    UQCV
    AI4CE
ArXivPDFHTML

Papers citing "Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows"

5 / 5 papers shown
Title
Single-model uncertainty quantification in neural network potentials
  does not consistently outperform model ensembles
Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles
Aik Rui Tan
S. Urata
Samuel Goldman
Johannes C. B. Dietschreit
Rafael Gómez-Bombarelli
BDL
38
42
0
02 May 2023
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing,
  and Improving Uncertainty Quantification
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification
Youngseog Chung
I. Char
Han Guo
J. Schneider
W. Neiswanger
38
70
0
21 Sep 2021
Fourier Neural Operator for Parametric Partial Differential Equations
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
226
2,287
0
18 Oct 2020
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
276
5,661
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
285
9,138
0
06 Jun 2015
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