Scholarlink

Deep neural networks (DNNs) employ successive function compositions of affine mappings and nonlinear activation function operations to create approximations for general functions. The coefficients in the affine mappings comprise the neural networks’ trainable parameters in machine learning methods.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Deep Neural Network Learning for PDE Solutions

  • 章节

  • 发表日期：

    2025年

查看全文
  • Wei Cai

摘要

Deep neural networks (DNNs) employ successive function compositions of affine mappings and nonlinear activation function operations to create approximations for general functions. The coefficients in the affine mappings comprise the neural networks’ trainable parameters in machine learning methods.