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Bayesian Nonlocal Operator Regression (BNOR): A Data-Driven Learning
  Framework of Nonlocal Models with Uncertainty Quantification

Bayesian Nonlocal Operator Regression (BNOR): A Data-Driven Learning Framework of Nonlocal Models with Uncertainty Quantification

6 October 2022
Yiming Fan
M. DÉlia
Yue Yu
H. Najm
Stewart Silling
ArXivPDFHTML

Papers citing "Bayesian Nonlocal Operator Regression (BNOR): A Data-Driven Learning Framework of Nonlocal Models with Uncertainty Quantification"

6 / 6 papers shown
Title
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in
  learning nonlocal operators
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators
Yiming Fan
H. Najm
Yue Yu
Stewart Silling
M. DÉlia
UQCV
28
0
0
27 Oct 2024
Learning Latent Space Dynamics with Model-Form Uncertainties: A
  Stochastic Reduced-Order Modeling Approach
Learning Latent Space Dynamics with Model-Form Uncertainties: A Stochastic Reduced-Order Modeling Approach
Jin Yi Yong
Rudy Geelen
Johann Guilleminot
26
1
0
30 Aug 2024
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model
  for Complex Material Responses
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses
S. Jafarzadeh
Stewart Silling
Ning Liu
Zhongqiang Zhang
Yue Yu
AI4CE
21
15
0
11 Jan 2024
Nonparametric learning of kernels in nonlocal operators
Nonparametric learning of kernels in nonlocal operators
Fei Lu
Qi An
Yue Yu
35
18
0
23 May 2022
Data-driven learning of nonlocal models: from high-fidelity simulations
  to constitutive laws
Data-driven learning of nonlocal models: from high-fidelity simulations to constitutive laws
Huaiqian You
Yue Yu
Stewart Silling
M. DÉlia
35
32
0
08 Dec 2020
The Bayesian Formulation and Well-Posedness of Fractional Elliptic
  Inverse Problems
The Bayesian Formulation and Well-Posedness of Fractional Elliptic Inverse Problems
Nicolas García Trillos
D. Sanz-Alonso
18
24
0
16 Nov 2016
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