pyfaust-torch
Advanced tools
The FAµST toolbox provides algorithms and data structures to decompose a given dense matrix into a product of sparse matrices in order to reduce its computational complexity (both for storage and manipulation).
FaµST can be used to:
speed up / reduce the memory footprint of iterative algorithms commonly used for solving high dimensional linear inverse problems,
learn dictionaries with an intrinsically efficient implementation,
compute (approximate) fast Fourier transforms on graphs.
FAQs
FAµST python toolbox
We found that pyfaust-torch demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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