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Ryan Sweke

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Potential and limitations of random Fourier features for dequantizing quantum machine learning

Sep 20, 2023
Ryan Sweke, Erik Recio, Sofiene Jerbi, Elies Gil-Fuster, Bryce Fuller, Jens Eisert, Johannes Jakob Meyer

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Classical Verification of Quantum Learning

Jun 08, 2023
Matthias C. Caro, Marcel Hinsche, Marios Ioannou, Alexander Nietner, Ryan Sweke

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On the average-case complexity of learning output distributions of quantum circuits

May 09, 2023
Alexander Nietner, Marios Ioannou, Ryan Sweke, Richard Kueng, Jens Eisert, Marcel Hinsche, Jonas Haferkamp

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A super-polynomial quantum-classical separation for density modelling

Oct 26, 2022
Niklas Pirnay, Ryan Sweke, Jens Eisert, Jean-Pierre Seifert

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Scalably learning quantum many-body Hamiltonians from dynamical data

Sep 28, 2022
Frederik Wilde, Augustine Kshetrimayum, Ingo Roth, Dominik Hangleiter, Ryan Sweke, Jens Eisert

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A single $T$-gate makes distribution learning hard

Jul 07, 2022
Marcel Hinsche, Marios Ioannou, Alexander Nietner, Jonas Haferkamp, Yihui Quek, Dominik Hangleiter, Jean-Pierre Seifert, Jens Eisert, Ryan Sweke

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Learnability of the output distributions of local quantum circuits

Oct 11, 2021
Marcel Hinsche, Marios Ioannou, Alexander Nietner, Jonas Haferkamp, Yihui Quek, Dominik Hangleiter, Jean-Pierre Seifert, Jens Eisert, Ryan Sweke

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Encoding-dependent generalization bounds for parametrized quantum circuits

Jun 07, 2021
Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, Ryan Sweke

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The effect of data encoding on the expressive power of variational quantum machine learning models

Aug 19, 2020
Maria Schuld, Ryan Sweke, Johannes Jakob Meyer

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On the Quantum versus Classical Learnability of Discrete Distributions

Jul 28, 2020
Ryan Sweke, Jean-Pierre Seifert, Dominik Hangleiter, Jens Eisert

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