AI/ML and Physics - Choosing What to Model in Physics-Informed Machine Learning

AI/ML and Physics - Choosing What to Model in Physics-Informed Machine Learning

Steve Brunton via YouTube Direct link

Intro

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1 of 17

Intro

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AI/ML and Physics - Choosing What to Model in Physics-Informed Machine Learning

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  1. 1 Intro
  2. 2 Deciding on the Problem
  3. 3 Why do you need an ML Model?
  4. 4 Case Study: Super Resolution
  5. 5 Case Study: Discovering New Physics
  6. 6 Case Study: Materials Discovery
  7. 7 Case Study: Computational Chemistry
  8. 8 Case Study: Digital Twins & Discrepancy Models
  9. 9 Case Study: Shape Optimization
  10. 10 The Digital Twin
  11. 11 Modeling the Math
  12. 12 Modeling the Chaos
  13. 13 Case Study: Climate Modeling
  14. 14 Benchmark Systems
  15. 15 Case Study: Turbulence Closure Modeling
  16. 16 When not to use Machine Learning
  17. 17 Outro

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