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Uncertainty Quantification in Multivariable Regression for Material
  Property Prediction with Bayesian Neural Networks

Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks

4 November 2023
Longze Li
Jiang Chang
Aleksandar Vakanski
Yachun Wang
Tiankai Yao
Min Xian
    AI4CE
ArXivPDFHTML

Papers citing "Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks"

4 / 4 papers shown
Title
Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning
Jiang Chang
Deekshith Basvoju
Aleksandar Vakanski
Indrajit Charit
Min Xian
AI4CE
39
0
0
28 Jan 2025
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and
  Inverse PDE Problems with Noisy Data
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang
Xuhui Meng
George Karniadakis
PINN
186
763
0
13 Mar 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
5,695
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
287
9,167
0
06 Jun 2015
1