marianneke / tensor-networks

References for the PyData 2019 presentation "the physics of deep learning using tensor networks"

tensor-networks further reading

References for the PyData 2019 presentation "the physics of deep learning using tensor networks"

Popular reading

• Physics today article (2019)
• MIT Tech Review article (2016)

Python library: tensornetwork

• Github
• Blog post (2019)
• initial arXiv paper (2019)
• arXiv paper with ML application (2019)
• arXiv paper with physics application: spin chains (2019)
• arXiv paper with physics application: entanglement renormalization for quantum critical lattice models (2019)

Renormalization Group / ML

• Mehta et al (2014)

Entanglement Measures

• Plenio et al (2005)
• Cui et al (2016): "quantum min cut / max flow"

Tensor Networks / ML

• Stoudenmire et al (2016)
• Levine et al (2017)