| Rank bounds for approximating gaussian densities in the tensor-train format PB Rohrbach, S Dolgov, L Grasedyck, R Scheichl SIAM/ASA Journal on Uncertainty Quantification 10 (3), 1191-1224, 2022 | 23 | 2022 |
| Inference, prediction and optimization of non-pharmaceutical interventions using compartment models: the PyRoss library R Adhikari, A Bolitho, F Caballero, ME Cates, J Dolezal, T Ekeh, J Guioth, ... arXiv preprint arXiv:2005.09625, 2020 | 15 | 2020 |
| Correction of coarse-graining errors by a two-level method: Application to the Asakura-Oosawa model H Kobayashi, PB Rohrbach, R Scheichl, NB Wilding, RL Jack The Journal of Chemical Physics 151 (14), 2019 | 11 | 2019 |
| Critical point for demixing of binary hard spheres H Kobayashi, PB Rohrbach, R Scheichl, NB Wilding, RL Jack Physical Review E 104 (4), 044603, 2021 | 9 | 2021 |
| Efficient Bayesian inference of fully stochastic epidemiological models with applications to COVID-19 YI Li, G Turk, PB Rohrbach, P Pietzonka, J Kappler, R Singh, J Dolezal, ... Royal Society Open Science 8 (8), 211065, 2021 | 8 | 2021 |
| Multilevel simulation of hard-sphere mixtures PB Rohrbach, H Kobayashi, R Scheichl, NB Wilding, RL Jack The Journal of Chemical Physics 157 (12), 2022 | 3 | 2022 |
| Convergence of random-weight sequential Monte Carlo methods PB Rohrbach, RL Jack arXiv preprint arXiv:2208.12108, 2022 | 3 | 2022 |
| Multilevel Monte Carlo simulation of soft matter using coarse-grained models P Rohrbach | | 2023 |
| Data for" Efficient Bayesian inference of fully stochastic epidemiological models with applications to COVID-19" YI Li, G Turk, P Rohrbach, P Pietzonka, J Kappler, R Singh, J Dolezal, ... | | 2021 |
