Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 01, 2019
Source ID
10.1016/j.jcp.2018.10.045

Entities

People

  • G.e. Karniadakis
  • Maziar Raissi
  • Paris Perdikaris

Organizations

  • Air Force Office of Scientific Research
  • Defense Advanced Research Projects Agency
  • United States Department of Energy

Tags

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks