| Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics A Ullah, PO Dral Nature communications 13 (1), 1930, 2022 | 34 | 2022 |
| Speeding up quantum dissipative dynamics of open systems with kernel methods A Ullah, PO Dral New Journal of Physics 23 (11), 113019, 2021 | 26 | 2021 |
| A comparative study of different machine learning methods for dissipative quantum dynamics LEH Rodríguez, A Ullah, KJR Espinosa, PO Dral, AA Kananenka Machine Learning: Science and Technology 3 (4), 045016, 2022 | 18 | 2022 |
| Stochastic equation of motion approach to fermionic dissipative dynamics. I. Formalism L Han, A Ullah, YA Yan, X Zheng, YJ Yan, V Chernyak The Journal of Chemical Physics 152 (20), 2020 | 16 | 2020 |
| Stochastic equation of motion approach to fermionic dissipative dynamics. II. Numerical implementation A Ullah, L Han, YA Yan, X Zheng, YJ Yan, V Chernyak The Journal of Chemical Physics 152 (20), 2020 | 16 | 2020 |
| One-Shot Trajectory Learning of Open Quantum Systems Dynamics A Ullah, PO Dral The Journal of Physical Chemistry Letter 13 (26), 6037–6041, 2022 | 12 | 2022 |
| Four-dimensional-spacetime atomistic artificial intelligence models F Ge, L Zhang, YF Hou, Y Chen, A Ullah, PO Dral The Journal of Physical Chemistry Letters 14 (34), 7732-7743, 2023 | 9 | 2023 |
| Quantum entanglement of parallel-coupled double quantum dots: A theoretical study using the hierarchical equations of motion approach H Gong, A Ullah, LZ Ye, X Zheng, YJ Yan Chinese Journal of Chemical Physics 31 (4), 510-516, 2018 | 8 | 2018 |
| Excited-state dynamics with machine learning L Zhang, A Ullah, M Pinheiro Jr, PO Dral, M Barbatti Quantum Chemistry in the Age of Machine Learning, 329-353, 2023 | 7 | 2023 |
| MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows PO Dral, F Ge, YF Hou, P Zheng, Y Chen, M Barbatti, O Isayev, C Wang, ... Journal of Chemical Theory and Computation, 2024 | 6 | 2024 |
| MLQD: A package for machine learning-based quantum dissipative dynamics A Ullah, PO Dral Computer Physics Communications 294, 108940, 2024 | 6 | 2024 |
| QD3SET-1: a database with quantum dissipative dynamics datasets A Ullah, LE Herrera Rodríguez, PO Dral, AA Kananenka Frontiers in Physics 11, 1223973, 2023 | 3 | 2023 |
| Call for urgent regulations on artificial intelligence PO Dral, A Ullah Available at SSRN 4418449, 2023 | 1 | 2023 |
| MONTE CARLO METHOD FOR SOLVING STOCHASTIC DIFFERENTIAL EQUATIONS A Ullah Quaid-i-Azam University, Pakistan, 2019 | 1 | 2019 |
| Quantum state fusion via generalized measurement Y Huang, M Yang, Z Lin, XK Li, A Ullah, ZL Cao Physics Letters A, 129492, 2024 | | 2024 |
| AI-enhanced on-the-fly simulation of nonlinear time-resolved spectra SV Pios, MF Gelin, A Ullah, PO Dral, L Chen arXiv preprint arXiv:2401.07399, 2024 | | 2024 |
| Monte-Carlo simulation of a stochastic differential equation A Ullah, K Majid, M Kamran, R Khan, Z Sheng Plasma Science and Technology 19 (12), 125001, 2017 | | 2017 |
Pavlo O. DralProfessor, Xiamen UniversityVerified email at xmu.edu.cn
