Tensor Networks for Machine Learning and Applications

Tensor Networks for Machine Learning and Applications

Institute for Pure & Applied Mathematics (IPAM) via YouTube Direct link

Models

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3 of 21

Models

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Tensor Networks for Machine Learning and Applications

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  1. 1 Introduction
  2. 2 Quantitization
  3. 3 Models
  4. 4 Whats Appealing
  5. 5 Benefits
  6. 6 Notation
  7. 7 Tensor Train
  8. 8 Quantum Physics
  9. 9 General Power Tools
  10. 10 Machine Learning
  11. 11 Infinite Matrix Product States
  12. 12 Locally Purified States
  13. 13 Projected entangled pair states
  14. 14 Fixed mirror layers
  15. 15 Why should tensor networks work
  16. 16 Mutual information of image data
  17. 17 Algorithms
  18. 18 Local update
  19. 19 Density matrix
  20. 20 Applications
  21. 21 Downsides

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