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TensorNetwork: A Library for Physics and Machine Learning

Computational Physics 2019-05-07 v1 Strongly Correlated Electrons Machine Learning High Energy Physics - Theory Machine Learning

Abstract

TensorNetwork is an open source library for implementing tensor network algorithms. Tensor networks are sparse data structures originally designed for simulating quantum many-body physics, but are currently also applied in a number of other research areas, including machine learning. We demonstrate the use of the API with applications both physics and machine learning, with details appearing in companion papers.

Keywords

Cite

@article{arxiv.1905.01330,
  title  = {TensorNetwork: A Library for Physics and Machine Learning},
  author = {Chase Roberts and Ashley Milsted and Martin Ganahl and Adam Zalcman and Bruce Fontaine and Yijian Zou and Jack Hidary and Guifre Vidal and Stefan Leichenauer},
  journal= {arXiv preprint arXiv:1905.01330},
  year   = {2019}
}

Comments

The TensorNetwork library can be found at https://github.com/google/tensornetwork

R2 v1 2026-06-23T08:56:37.951Z