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User guide
1. Quick-Start
1.1. Organization of TensorLy
1.2. TensorLy Backend
1.3. Tensor manipulation
1.4. Tensor algebra
1.5. Tensor decomposition
1.6. Tensor regressions
1.7. Metrics
1.8. Sampling random tensors
1.9. Experimental features
1.10. Datasets
2. TensorLy’s backend system
2.1. Backend?
2.2. Why backends?
2.3. How do I change the backend?
2.4. Context of a tensor
2.5. Basic functions
2.6. Case study: TensorLy and PyTorch
2.6.1. On CPU
2.6.2. On GPU
3. Tensor basics
3.1. Creating a tensor
3.2. Unfolding
3.3. Folding
3.4. References
4. Tensor decomposition
4.1. CP form of a tensor
4.1.1. CANDECOMP-PARAFAC decomposition
4.2. Tucker form of a tensor
4.2.1. Tucker decomposition
4.3. Matrix-Product-State / Tensor-Train Decomposition
4.3.1. Implementations
4.4. References
5. Tensor regression
5.1. Setting
5.2. References
6. Sparse Backend
6.1. Why a separate sparse backend?
6.2. Algorithms
6.2.1. Usage
6.3. Missing Values
6.3.1. Example
Installing tensorly
1.
Quick-Start