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