Pennylane: Automatic differentiation of hybrid quantum-classical computations V Bergholm, J Izaac, M Schuld, C Gogolin, S Ahmed, V Ajith, MS Alam, ... arXiv preprint arXiv:1811.04968, 2018 | 486 | 2018 |
Effect of data encoding on the expressive power of variational quantum-machine-learning models M Schuld, R Sweke, JJ Meyer Physical Review A 103 (3), 032430, 2021 | 276 | 2021 |
Stochastic gradient descent for hybrid quantum-classical optimization R Sweke, F Wilde, J Meyer, M Schuld, PK Fährmann, ... Quantum 4, 314, 2020 | 181 | 2020 |
Fisher information in noisy intermediate-scale quantum applications JJ Meyer Quantum 5, 539, 2021 | 55 | 2021 |
Encoding-dependent generalization bounds for parametrized quantum circuits MC Caro, E Gil-Fuster, JJ Meyer, J Eisert, R Sweke Quantum 5, 582, 2021 | 45 | 2021 |
Training quantum embedding kernels on near-term quantum computers T Hubregtsen, D Wierichs, E Gil-Fuster, PJHS Derks, PK Faehrmann, ... Physical Review A 106 (4), 042431, 2022 | 37 | 2022 |
A variational toolbox for quantum multi-parameter estimation JJ Meyer, J Borregaard, J Eisert npj Quantum Information 7 (1), 89, 2021 | 34 | 2021 |
Exploiting symmetry in variational quantum machine learning JJ Meyer, M Mularski, E Gil-Fuster, AA Mele, F Arzani, A Wilms, J Eisert PRX Quantum 4 (1), 010328, 2023 | 31 | 2023 |
Exponentially tighter bounds on limitations of quantum error mitigation Y Quek, DS França, S Khatri, JJ Meyer, J Eisert arXiv preprint arXiv:2210.11505, 2022 | 9 | 2022 |
Classical surrogates for quantum learning models FJ Schreiber, J Eisert, JJ Meyer arXiv preprint arXiv:2206.11740, 2022 | 9 | 2022 |
Gradients just got more flexible JJ Meyer Quantum Views 5, 50, 2021 | 2 | 2021 |
Quantencomputer heute und in naher Zukunft: eine realistische Perspektive PK Fährmann, JJ Meyer, J Eisert Chancen und Risiken von Quantentechnologien: Praxis der zweiten …, 2023 | | 2023 |