| Gaussian process states: A data-driven representation of quantum many-body physics A Glielmo*, Y Rath*, G Csányi, A De Vita, GH Booth Physical Review X 10 (4), 041026, 2020 | 22 | 2020 |
| A Bayesian inference framework for compression and prediction of quantum states Y Rath, A Glielmo, GH Booth The Journal of chemical physics 153 (12), 2020 | 15 | 2020 |
| Quantum Gaussian process state: A kernel-inspired state with quantum support data Y Rath, GH Booth Physical Review Research 4 (2), 023126, 2022 | 11 | 2022 |
| Framework for efficient ab initio electronic structure with Gaussian Process States Y Rath, GH Booth Physical Review B 107 (20), 205119, 2023 | 7 | 2023 |
| Prominent interference peaks in the dephasing Anderson model Y Rath, F Mintert Physical Review Research 2 (2), 023161, 2020 | 4 | 2020 |
| Impact of conditional modelling for a universal autoregressive quantum state M Bortone, Y Rath, GH Booth Quantum 8, 1245, 2024 | 2 | 2024 |
| Fast and accurate nonadiabatic molecular dynamics enabled through variational interpolation of correlated electron wavefunctions K Atalar, Y Rath, R Crespo-Otero, GH Booth arXiv preprint arXiv:2403.12275, 2024 | | 2024 |
| Characterizing frequency fluctuations induced non-Markovian noise in superconducting qubits A Agarwal, L Lindoy, Y Rath, D Lall, I Rungger Bulletin of the American Physical Society, 2024 | | 2024 |
| Interpolating many-body wave functions for accelerated molecular dynamics on near-exact electronic surfaces Y Rath, GH Booth arXiv preprint arXiv:2402.11097, 2024 | | 2024 |
| Bayesian Modelling Approaches for Quantum States - The Ultimate Gaussian Process States Handbook Y Rath King's College London, 2023 | | 2023 |
George BoothKing's College LondonVerified email at kcl.ac.uk
