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https://github.com/tensorly/tensorly/blob/master/tensorly/decomposition/candecomp_parafac.py#L154
I think this line is wrong - there should be `factors` on the left hand side, not `factor`.
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#### Describe the bug
In tensorly 0.5.1 installed from the Anaconda channel, non-negative PARAFAC with normalization returns NaNs as a result when run on GPU using PyTorch 1.8.1 as the backend. Non…
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#### Problem
In response to #72 and for a few months now, Tensorly has allowed to fix some modes in decompositions, e.g. using the following syntax for parafac:
```python
out = parafac(tensor, rank…
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Some of the tests are randomly failing and either they, or the underlying function being tested, needs to be fixed, this issue tracks the progress and remaining work to be done.
# Tracking the test…
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Even run with the same input array and parameters, the factors of parafac result would be changed. Might the randomness nature is inevitable. We might average the loadings after repeating 100 times, …
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I'm a new user of LIANA+ and currently working with a large dataset that includes approximately 300 samples (around 1.5 million cells). I have access to 4 GPUs, each with 48 GB of memory. I’m consider…
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We probably need to add some more examples and doc for new features in TensorLy.
Would be great for instance to have an example for @earmingol @hmbaghdassarian as a user guide on how to use the Co…
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# Adding an optimization module
For now, Tensorly (TL) ships with one API for each particular tensor decomposition model. While this has the advantage of simplicity for the end-user, this limits the …
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See #298. Several of the tests for methods should be extended to the complex cases. Perhaps a first step to accomplishing this is to extend the random tensor methods to be able to construct random ten…
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Not a stats expert, so perhaps I'm just not understanding. But in the anova function for both glm and lm, whenever I compare two models, no matter what the formulas are, it always reports the differen…