DeepONet.pdf

1910.03193.pdf
Preview of DeepONet
🔗 Source: arxiv.org
📊 Size: 740 KB
📄 Pages: 22 pages
⬇️ Downloads: 80

Summary

DeepONet learns nonlinear operators for identifying differential equations based on the universal approximation theorem of operators, using two sub-networks: a branch net for encoding input functions and a trunk net for encoding output function locations, achieving high-order error convergence and significantly reducing generalization error compared to fully-connected networks.

Description

DeepONet learns nonlinear operators for identifying differential equations based on the universal approximation theorem of operators, using two sub-networks: a...

Technical Information

  • File Format: PDF
  • File Size: 740 KB
  • Pages: 22
  • Language: EN
  • Total Downloads: 80
  • Last Updated: 6 hours ago

Document Overview

This PDF document about DeepONet provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into DeepONet.

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