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Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition


Jan 19, 2023
Juan Carrasquilla, Mohamed Hibat-Allah, Estelle Inack, Alireza Makhzani, Kirill Neklyudov, Graham W. Taylor, Giacomo Torlai

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* 10 pages, 6 figures. Minimal implementation: https://github.com/carrasqu/binncode 

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Supplementing Recurrent Neural Network Wave Functions with Symmetry and Annealing to Improve Accuracy


Jul 28, 2022
Mohamed Hibat-Allah, Roger G. Melko, Juan Carrasquilla

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* Machine Learning and the Physical Sciences, NeurIPS 2021 
* 11 pages, 4 figures, 1 table. Originally published in Machine Learning and the Physical Sciences Workshop (NeurIPS 2021), see: https://ml4physicalsciences.github.io/2021/files/NeurIPS_ML4PS_2021_92.pdf. Our reproducibility code can be found on https://github.com/mhibatallah/RNNWavefunctions 

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Neural Error Mitigation of Near-Term Quantum Simulations


May 17, 2021
Elizabeth R. Bennewitz, Florian Hopfmueller, Bohdan Kulchytskyy, Juan Carrasquilla, Pooya Ronagh

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* 18 pages, 4 main figures, 6 supplementary figures, 1 supplementary table 

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Variational Neural Annealing


Jan 25, 2021
Mohamed Hibat-Allah, Estelle M. Inack, Roeland Wiersema, Roger G. Melko, Juan Carrasquilla

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* 19 pages, 9 figures, 1 table 

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Attention-based Quantum Tomography


Jun 22, 2020
Peter Cha, Paul Ginsparg, Felix Wu, Juan Carrasquilla, Peter L. McMahon, Eun-Ah Kim

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Watch and learn -- a generalized approach for transferrable learning in deep neural networks via physical principles


Mar 03, 2020
Kyle Sprague, Juan Carrasquilla, Steve Whitelam, Isaac Tamblyn

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