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Hi. I test the CP decomposition and I met a mistake returned by parafac:
`last, first, vertical, horizontal = parafac(W, rank=rank, init='random')
ValueError: not enough values to unpack (expected 4…
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The following methods are not related to authentication but may be of interest to some users and would be useful to include in a chemometric toolbox.
- Piecewise Direct Standardization (https://pub…
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The parafac test suite compares a tensor to expected data by comparing two sets of values. This results in equality comparison which is too fragile for floating point values. There's also the problem …
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I use pytorch 1.10 and tensorly 0.4.0.,but I got error as following:
File "/content/drive/MyDrive/Tensor_decomposing/decompositions.py", line 14, in cp_decomposition_conv_layer
parafac(layer.weight.…
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#### Steps or Code to Reproduce
```python
import tensorly as tl
import ivy
tl.set_backend("numpy")
a = tl.ones((2,3,4))
z = tl.decomposition.randomised_parafac(a, 2, 1, n_iter_max=1, init="svd",…
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#### Describe the bug
Hi, the problem i would like to raised is that when registering the sparse backend in numpy_backend.py, there is always throughing the issues with no attribute found for 'where'…
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#### Is your feature request related to a problem? Please describe.
Dear Tensorly team,
I am using your package for my research, I am applying non-negative PARAFAC to my data. And in my dataset …
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Hi! I am currently working with PARAFAC2 and I noticed there is no support for missing data (PARAFAC has the `mask` argument). Are there any plans for missing data support for PARAFAC2? If not, I woul…
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Hi there, thank you making my life easier with tlviz. I was wondering, would there be interest in updates of functions in `factor_tools.py` to support `PARAFAC2Tensor`s?