| Exponential concentration and untrainability in quantum kernel methods S Thanasilp, S Wang, M Cerezo, Z Holmes arXiv preprint arXiv:2208.11060, 2022 | 67 | 2022 |
| Subtleties in the trainability of quantum machine learning models S Thanasilp, S Wang, NA Nghiem, P Coles, M Cerezo Quantum Machine Intelligence 5 (1), 21, 2023 | 45 | 2023 |
| Qubit-efficient encoding schemes for binary optimisation problems B Tan, MA Lemonde, S Thanasilp, J Tangpanitanon, DG Angelakis Quantum 5, 454, 2021 | 29 | 2021 |
| Expressibility and trainability of parametrized analog quantum systems for machine learning applications J Tangpanitanon, S Thanasilp, N Dangniam, MA Lemonde, DG Angelakis Physical Review Research 2 (4), 043364, 2020 | 29 | 2020 |
| Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing M Cerezo, M Larocca, D García-Martín, NL Diaz, P Braccia, E Fontana, ... arXiv preprint arXiv:2312.09121, 2023 | 23 | 2023 |
| Trainability barriers and opportunities in quantum generative modeling MS Rudolph, S Lerch, S Thanasilp, O Kiss, S Vallecorsa, M Grossi, ... arXiv preprint arXiv:2305.02881, 2023 | 12 | 2023 |
| Signatures of a sampling quantum advantage in driven quantum many-body systems J Tangpanitanon, S Thanasilp, MA Lemonde, N Dangniam, DG Angelakis Quantum Science and Technology 8 (2), 025019, 2023 | 5 | 2023 |
| Quantum supremacy and quantum phase transitions S Thanasilp, J Tangpanitanon, MA Lemonde, N Dangniam, DG Angelakis Physical Review B 103 (16), 165132, 2021 | 5 | 2021 |
| On fundamental aspects of quantum extreme learning machines W Xiong, G Facelli, M Sahebi, O Agnel, T Chotibut, S Thanasilp, Z Holmes arXiv preprint arXiv:2312.15124, 2023 | 4 | 2023 |
| Quantum supremacy with analog quantum processors for material science and machine learning J Tangpanitanon, S Thanasilp, MA Lemonde, DG Angelakis arXiv preprint arXiv:1906.03860, 2019 | 3 | 2019 |
| Efficiently extracting multi-point correlations of a floquet thermalized system YG Zheng, WY Zhang, YC Shen, A Luo, Y Liu, MG He, HR Zhang, W Lin, ... arXiv preprint arXiv:2210.08556, 2022 | 2 | 2022 |
| A unified framework for trace-induced quantum kernels BY Gan, D Leykam, S Thanasilp arXiv preprint arXiv:2311.13552, 2023 | 1 | 2023 |
| Variational quantum simulation: a case study for understanding warm starts M Drudis, S Thanasilp, Z Holmes arXiv preprint arXiv:2404.10044, 2024 | | 2024 |
| Potentials and Limitations of Analog Quantum Simulators in Variational Quantum Algorithms K Srimahajariyapong, S Thanasilp, T Chotibut Bulletin of the American Physical Society, 2024 | | 2024 |
| arXiv: Trainability barriers and opportunities in quantum generative modeling MS Rudolph, S Lerch, Z Holmes, S Vallecorsa, S Thanasilp, M Grossi, ... | | 2023 |
| Expressivity and generalization error of projected fidelity quantum kernels BY Gan, S Thanasilp, D Leykam, D Angelakis APS March Meeting Abstracts 2023, D73. 007, 2023 | | 2023 |
| Qubit-efficient encoding schemes for binary optimisation problems B Tan, MA Lemonde, S Thanasilp, J Tangpanitanon, D Angelakis Bulletin of the American Physical Society, 2021 | | 2021 |
| Quantum supremacy and quantum phase transitions S Thanasilp, J Tangpanitanon, MA Lemonde, N Dangniam, D Angelakis Bulletin of the American Physical Society, 2021 | | 2021 |
| Quantum supremacy in driven quantum many-body systems J Tangpanitanon, S Thanasilp, MA Lemonde, N Dangniam, D Angelakis APS March Meeting Abstracts 2021, F32. 012, 2021 | | 2021 |
Dimitris G. AngelakisPrincipal Investigator, Centre for Quantum Technologies Singapore & Assoc. Prof. Technical U CreteVerified email at ece.tuc.gr
