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Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
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HomPINNs:用于解决多个解决方案的非线性微分方程的反向问题的同位素物理信息的神经网络

Haoyang Zheng1, Yao Huang2, Ziyang Huang3

  • 1School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.

Journal of computational physics
|January 29, 2024
PubMed
概括

同位体物理信息神经网络 (HomPINNs) 解决了多个解决方案的非线性微分方程的复杂反向问题. 这种新的框架有效地识别了科学计算应用中的各种解决方案和未知的参数.

关键词:
同一类型的延续方法.机器学习是机器学习.多个解决方案多个解决方案非线性微分方程的非线性微分方程.基于物理学的神经网络.

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