| 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 | 781 | 2018 |
| Quantum evolution kernel: Machine learning on graphs with programmable arrays of qubits LP Henry, S Thabet, C Dalyac, L Henriet Physical Review A 104 (3), 032416, 2021 | 36 | 2021 |
| Quantum feature maps for graph machine learning on a neutral atom quantum processor B Albrecht, C Dalyac, L Leclerc, L Ortiz-Gutiérrez, S Thabet, ... Physical Review A 107 (4), 042615, 2023 | 19 | 2023 |
| Classically approximating variational quantum machine learning with random fourier features J Landman, S Thabet, C Dalyac, H Mhiri, E Kashefi arXiv preprint arXiv:2210.13200, 2022 | 19 | 2022 |
| Laplacian Eigenmaps with variational circuits: a quantum embedding of graph data S Thabet, JF Hullo arXiv preprint arXiv:2011.05128, 2020 | 5 | 2020 |
| Enhancing Graph Neural Networks with Quantum Computed Encodings S Thabet, R Fouilland, M Djellabi, I Sokolov, S Kasture, LP Henry, ... arXiv preprint arXiv:2310.20519, 2023 | 3 | 2023 |
| Extending Graph Transformers with Quantum Computed Aggregation S Thabet, R Fouilland, L Henriet arXiv preprint arXiv:2210.10610, 2022 | 3 | 2022 |
| Constrained and Vanishing Expressivity of Quantum Fourier Models H Mhiri, L Monbroussou, M Herrero-Gonzalez, S Thabet, E Kashefi, ... arXiv preprint arXiv:2403.09417, 2024 | | 2024 |
