| Expressibility of the alternating layered ansatz for quantum computation K Nakaji, N Yamamoto Quantum 5, 434, 2021 | 107 | 2021 |
| Faster amplitude estimation K Nakaji Quantum Information & Computation 20 (13-14), 1109-1123, 2020 | 61 | 2020 |
| Approximate amplitude encoding in shallow parameterized quantum circuits and its application to financial market indicators K Nakaji, S Uno, Y Suzuki, R Raymond, T Onodera, T Tanaka, H Tezuka, ... Physical Review Research 4 (2), 023136, 2022 | 58 | 2022 |
| Quantum semi-supervised generative adversarial network for enhanced data classification K Nakaji, N Yamamoto Scientific reports 11 (1), 19649, 2021 | 32 | 2021 |
| Grover search revisited: Application to image pattern matching H Tezuka, K Nakaji, T Satoh, N Yamamoto Physical Review A 105 (3), 032440, 2022 | 31 | 2022 |
| Overfitting in quantum machine learning and entangling dropout M Kobayashi, K Nakaji, N Yamamoto Quantum Machine Intelligence 4 (2), 30, 2022 | 14 | 2022 |
| Quantum-classical hybrid neural networks in the neural tangent kernel regime K Nakaji, H Tezuka, N Yamamoto Quantum Science and Technology 9 (1), 015022, 2023 | 9* | 2023 |
| Fast quantum algorithm for differential equations M Bagherimehrab, K Nakaji, N Wiebe, A Aspuru-Guzik arXiv preprint arXiv:2306.11802, 2023 | 6 | 2023 |
| Measurement optimization of variational quantum simulation by classical shadow and derandomization K Nakaji, S Endo, Y Matsuzaki, H Hakoshima Quantum 7, 995, 2023 | 6 | 2023 |
| qSWIFT: High-order randomized compiler for Hamiltonian simulation K Nakaji, M Bagherimehrab, A Aspuru-Guzik arXiv preprint arXiv:2302.14811, 2023 | 5* | 2023 |
| Deterministic and random features for large-scale quantum kernel machine K Nakaji, H Tezuka, N Yamamoto arXiv preprint arXiv:2209.01958, 2022 | 5 | 2022 |
| A composite measurement scheme for efficient quantum observable estimation ZJ Zhang, K Nakaji, M Choi, A Aspuru-Guzik arXiv preprint arXiv:2305.02439, 2023 | 3 | 2023 |
| Approximate complex amplitude encoding algorithm and its application to data classification problems N Mitsuda, K Nakaji, Y Suzuki, T Tanaka, R Raymond, H Tezuka, ... arXiv preprint arXiv:2211.13039, 2022 | 2 | 2022 |
| Expressive quantum supervised machine learning using Kerr-nonlinear parametric oscillators Y Mori, K Nakaji, Y Matsuzaki, S Kawabata Quantum Machine Intelligence 6 (1), 14, 2024 | 1 | 2024 |
| High-Order Randomized Compiler for Hamiltonian Simulation K Nakaji, M Bagherimehrab, A Aspuru-Guzik PRX Quantum 5 (2), 020330, 2024 | | 2024 |
| The generative quantum eigensolver (GQE) and its application for ground state search K Nakaji, LB Kristensen, JA Campos-Gonzalez-Angulo, MG Vakili, ... arXiv preprint arXiv:2401.09253, 2024 | | 2024 |
