tf-fsvd

Functional TensorFlow Implementation of Singular Value Decomposition for paper Fast Graph Learning (by samihaija)

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Posts where tf-fsvd has been mentioned. We have used some of these posts to build our list of alternatives and similar projects - the last one was on 2021-02-23.
  • [R] TensorFlow Functional Implementation of Singular Value Decomposition (SVD)
    I think that a PyTorch should be straight-forward. IMO, the hardest part is to replicate the main fsvd function in PyTorch. If you could implement that, the implementation of "Product Functions" should be simple (e.g. see SparseMatrixPF or BlockWisePF, with <10 code lines excluding comments). I am also happy to collaborate. It is up to you, if you want to push your code directly onto tf-fsvd or create your own pytorch-fsvd and we can cross-link to each other.
    We have developed and open-sourced Singular Value Decomposition (SVD) Functional for TensorFlow (tf-fsvd) that computes SVD of a matrix M, without requiring explicit computation of M.

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samihaija/tf-fsvd is an open source project licensed under MIT License which is an OSI approved license.