-
Some tensor networks can have global symmetries like conserved U(1) of SU(2) charge.
The symmetry imposes a sparse block structure on the individual tensors, which can be exploited to speed up contr…
-
## Possibly 🐛 Bug
Maybe I'm using the API wrong (but params are identical for numpy and torch functions), but the [linked matrix](https://www.dropbox.com/s/sqmcrsl86e5ya70/invertme.npy?dl=0) result…
-
Block sparsity is needed for many physics applications.
-
Facebook published reference code of fast NumPy randomized SVD (based on power iteration): https://github.com/facebook/fbpca/blob/master/fbpca.py#L1503
Only top eigenvectors are useful e.g. for spe…
-
Currently if you call gradients(ys, xs), it will return the sum of dy/dx over all ys for each x in xs. I believe this doesn't accord with an a priori mathematical notion of the derivative of a vector.…
-
@ahwillia Here is my plan for evaluating the tensor factorization code on prefrontal calcium imaging data:
1. Compare "naive" vs. "align" exports (per #226). In particular, I would like to do a det…
-
I have an application where there is a large tensor contraction in the inner loop, with some arrays that are fixed and others that are updated between iterations. Operations only involving the constan…
-
Has CTF implemented SVD or Higher-Order SVD method for either dense or sparse tensor ?
-
Do you plan to support tensor unfoldings in this package?
(Or is there a simple way to implement this using the current functionality of this package...? Excuse my ignorance if so.)
-
Let us document some key words for JuliaQuantum projects. Comment below if anything is missing or categorized badly or improper. Features have been implemented should also documented here. Details ca…