HCP-PIGN: Efficient heat conduction prediction by physics-informed graph convolutional neural network

Author:

Peng Jiang-Zhou,Aubry Nadine,Li Yu-Bai,Chen Zhi-Hua,Mei Mei,Hua Yue

Publisher

Elsevier BV

Reference42 articles.

1. On the application of physics informed neural networks (PINN) to solve boundary layer thermal-fluid problems;Bararnia;Int. Commun. Heat Mass Transf.,2022

2. A. G. Baydin and B. A. Pearlmutter, “Automatic differentiation of algorithms for machine learning,” arXiv Prepr. arXiv1404.7456, 2014.

3. Automatic differentiation in machine learning: a survey;Baydin;J. Marchine Learn. Res.,2018

4. Feature extraction and classification using deep convolutional neural networks;Bodapati;J. Cyber Secur. Mobil.,2019

5. A progressive batching L-BFGS method for machine learning;Bollapragada,2018

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