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Jordan Cotler

Analyzing Populations of Neural Networks via Dynamical Model Embedding

Feb 27, 2023
Jordan Cotler, Kai Sheng Tai, Felipe Hernández, Blake Elias, David Sussillo

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* 12+8 pages, 11 figures

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Hardware-efficient learning of quantum many-body states

Dec 12, 2022
Katherine Van Kirk, Jordan Cotler, Hsin-Yuan Huang, Mikhail D. Lukin

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* 7+28 pages, 6 figures

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The Complexity of NISQ

Oct 13, 2022
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li

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* 15+37 pages, 3 figures

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Revisiting dequantization and quantum advantage in learning tasks

Dec 06, 2021
Jordan Cotler, Hsin-Yuan Huang, Jarrod R. McClean

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* 6 pages, 1 figure; v2: further exposition added

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Quantum advantage in learning from experiments

Dec 01, 2021
Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean

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* 6 pages, 17 figures + 46 page appendix; open-source code available at https://github.com/quantumlib/ReCirq/tree/master/recirq/qml_lfe

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Exponential separations between learning with and without quantum memory

Nov 18, 2021
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li

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* 77 pages, 2 figures, many diagrams; accepted to FOCS 2021; v2: typos corrected

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A Hierarchy for Replica Quantum Advantage

Nov 10, 2021
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li

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* 3+17 pages, 2 figures

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