%0 Generic %1 roberts2019tensornetwork %A Roberts, Chase %A Milsted, Ashley %A Ganahl, Martin %A Zalcman, Adam %A Fontaine, Bruce %A Zou, Yijian %A Hidary, Jack %A Vidal, Guifre %A Leichenauer, Stefan %D 2019 %K macjin %T TensorNetwork: A Library for Physics and Machine Learning %U http://arxiv.org/abs/1905.01330 %X 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.

@misc{roberts2019tensornetwork, 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.}, added-at = {2019-07-29T12:45:52.000+0200}, author = {Roberts, Chase and Milsted, Ashley and Ganahl, Martin and Zalcman, Adam and Fontaine, Bruce and Zou, Yijian and Hidary, Jack and Vidal, Guifre and Leichenauer, Stefan}, biburl = {https://www.bibsonomy.org/bibtex/2f3204d4211db27d382c90b6071458aec/cmcneile}, description = {TensorNetwork: A Library for Physics and Machine Learning}, interhash = {0221f414b6b7e7e881c7fbb80c08a181}, intrahash = {f3204d4211db27d382c90b6071458aec}, keywords = {macjin}, note = {cite arxiv:1905.01330Comment: The TensorNetwork library can be found at https://github.com/google/tensornetwork}, timestamp = {2019-07-29T12:45:52.000+0200}, title = {TensorNetwork: A Library for Physics and Machine Learning}, url = {http://arxiv.org/abs/1905.01330}, year = 2019 }