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Johannes Jakob Meyer

Observed names: Johannes Meyer, Meyer, Johannes, Meyer, Johannes Jakob
ORCID: 0000-0003-1533-8015
Observed ORCID: 0000-0003-1533-8015
OpenAlex ID: A5079737237
PennyLane: Automatic differentiation of hybrid quantum-classical computations
2018 · Bergholm, Ville, Izaac, Josh, et al. · arXiv (Cornell University) · 794
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Effect of data encoding on the expressive power of variational quantum-machine-learning models
2021 · Maria Schuld, Ryan Sweke, et al. · Physical Review A · 748
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Stochastic gradient descent for hybrid quantum-classical optimization
2020 · Ryan Sweke, Frederik Wilde, et al. · Quantum · 219
Stochastic gradient descent for hybrid quantum-classical optimization
2020 · Sweke, Ryan, Sweke, Ryan, et al. · Refubium (Universitätsbibliothek der Freien Universität Berlin) · 203
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Exploiting Symmetry in Variational Quantum Machine Learning
2023 · Johannes Jakob Meyer, Marian Mularski, et al. · PRX Quantum · 172
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Training quantum embedding kernels on near-term quantum computers
2022 · Thomas Hubregtsen, David Wierichs, et al. · Physical Review A · 146
Fisher Information in Noisy Intermediate-Scale Quantum Applications
2021 · Johannes Jakob Meyer · Quantum · 125
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A variational toolbox for quantum multi-parameter estimation
2021 · Johannes Jakob Meyer, Johannes Borregaard, et al. · npj Quantum Information · 109
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Encoding-dependent generalization bounds for parametrized quantum circuits
2021 · Caro, Matthias C., Gil-Fuster, Elies, et al. · Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) · 104
Fisher Information in Noisy Intermediate-Scale Quantum Applications
2021 · Meyer, Johannes Jakob · Refubium (Universitätsbibliothek der Freien Universität Berlin) · 94
Exponentially tighter bounds on limitations of quantum error mitigation
2024 · Yihui Quek, Daniel Stilck França, et al. · Nature Physics · 91
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Classical Surrogates for Quantum Learning Models
2023 · Franz J. Schreiber, Jens Eisert, et al. · Physical Review Letters · 59
Potential and limitations of random Fourier features for dequantizing quantum machine learning
2025 · Ryan Sweke, Erik Recio-Armengol, et al. · Quantum · 21
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Exponentially tighter bounds on limitations of quantum error mitigation
2022 · Quek, Yihui, Fran\c{c}a, Daniel Stilck, et al. · arXiv (Cornell University) · 21
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Quantum Metrology in the Finite-Sample Regime
2025 · Johannes Jakob Meyer, Sumeet Khatri, et al. · PRX Quantum · 14
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Stochastic Gradient Descent for Hybrid Quantum-Classical Optimization
2020 · Frederik Wilde, Ryan Sweke, et al. · Bulletin of the American Physical Society · 8
Variational quantum algorithm for enhanced continuous variable optical phase sensing
2025 · Jens A. H. Nielsen, Mateusz J. Kicinski, et al. · npj Quantum Information · 5
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Single-shot quantum machine learning
2025 · Erik Recio-Armengol, Jens Eisert, et al. · Physical Review A · 4
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Classical Surrogates for Quantum Learning Models
2022 · Schreiber, Franz J., Eisert, Jens, et al. · PubMed · 4
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Encoding-dependent generalization bounds for parametrized quantum circuits
2021 · Matthias C. Caro, Elies Gil-Fuster, et al. · Quantum · 4
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Gradients just got more flexible
2021 · Johannes Jakob Meyer · 3
Tomography of Parametrized Quantum States
2025 · Franz J. Schreiber, Jens Eisert, et al. · PRX Quantum · 2
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Quantum metrology in the finite-sample regime
2023 · Meyer, Johannes Jakob, Khatri, Sumeet, et al. · arXiv (Cornell University) · 2
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Exponentially tighter bounds on limitations of quantum error mitigation
2022 · Quek, Yihui, França, Daniel Stilck, et al. · HAL · 2
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Potential and limitations of random Fourier features for dequantizing quantum machine learning
2023 · Sweke, Ryan, Recio-Armengol, Erik, et al. · arXiv (Cornell University) · 1
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Works count: 44
Citation count: 3,158
H-index: 15
I10-index: 16
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