| A reinforcement learning approach to rare trajectory sampling DC Rose, JF Mair, JP Garrahan New Journal of Physics 23 (1), 013013, 2021 | 67 | 2021 |
| Boundary conditions dependence of the phase transition in the quantum Newman-Moore model K Sfairopoulos, L Causer, JF Mair, JP Garrahan Physical Review B 108 (17), 174107, 2023 | 10 | 2023 |
| Cellular automata in dimensions and ground states of spin models in dimensions K Sfairopoulos, L Causer, JF Mair, JP Garrahan arXiv preprint arXiv:2309.08059, 2023 | 3 | 2023 |
| Rejection-free quantum Monte Carlo in continuous time from transition path sampling L Causer, K Sfairopoulos, JF Mair, JP Garrahan Physical Review B 109 (2), 024307, 2024 | 2 | 2024 |
| Training neural network ensembles via trajectory sampling JF Mair, DC Rose, JP Garrahan arXiv preprint arXiv:2209.11116, 2022 | 2 | 2022 |
| Minibatch training of neural network ensembles via trajectory sampling JF Mair, L Causer, JP Garrahan arXiv preprint arXiv:2306.13442, 2023 | | 2023 |
| Trajectory Ensembles and Machine Learning: From reinforcement learning for rare event sampling to training of neural network ensembles J Mair University of Nottingham, 0 | | |
Juan P. GarrahanProfessor of Physics, University of NottinghamVerified email at nottingham.ac.uk
