A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks 论文

2022Computer Methods in Applied Mechanics and Engineering引用 562
DOIPDF
Model Reduction and Neural NetworksNuclear reactor physics and engineeringGaussian Processes and Bayesian Inference
人工智能Gaussian Processes and Bayesian InferenceModel Reduction and Neural NetworksNuclear reactor physics and engineering
相关技术:Model Reduction and Neural NetworksGaussian Processes and Bayesian Inference
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发表期刊/会议
Computer Methods in Applied Mechanics and Engineering
发表日期
2022-10-22
发表年份
2022

关键词

Model Reduction and Neural NetworksNuclear reactor physics and engineeringGaussian Processes and Bayesian Inference
PDFDOIOpenAlex

作者查看全部 (5)

M

Min Zhu

L

Lu Lu

C

Chenxi Wu

Y

Yadhu Kartha

相关技术查看全部 (2)

Model Reduction and Neural NetworksGaussian Processes and Bayesian Inference

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