Daan Crommelin - Publications
For an overview of my publications, please check my ORCID page or my google scholar profile.
Some recent publications:
- Del Razo, M. J., Crommelin, D., & Bolhuis, P. G., 2024. Data-driven dynamical coarse-graining for condensed matter systems, Journal of Chemical Physics, 160(2) 024108 (link).
- Melchers, H., Crommelin, D., Koren, B., Menkovski, V., & Sanderse, B., 2023. Comparison of neural closure models for discretised PDEs, Computers & Mathematics with Applications, 143, 94-107 (link)
- Jansson, F., Van Den Oord, G., Pelupessy, I., Chertova, M., Grönqvist, J. H., Siebesma, A. P., & Crommelin, D., 2022. Representing cloud mesoscale variability in superparameterized climate models, Journal of Advances in Modeling Earth Systems, 14(8), e2021MS002892 (link)
- Gugole, F., Coffeng, L.E., Edeling, W., Sanderse, B., de Vlas, S.J. and Crommelin, D., 2021. Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model, PLoS Computational Biology 17 (9), e1009355 (link)
- Edeling, W., Arabnejad, H., Sinclair, R., Suleimenova, D., Gopalakrishnan, K., Bosak, B., Groen, D., Mahmood, I., Crommelin, D. and Coveney, P.V., 2021. The impact of uncertainty on predictions of the CovidSim epidemiological code, Nature Computational Science 1(2), pp.128-135 (link)
- Crommelin, D. and Edeling, W., 2021. Resampling with neural networks for stochastic parameterization in multiscale systems, Physica D: Nonlinear Phenomena, 422, p.132894 (link)
- Groen, D., et al., 2021. VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations, Philosophical Transactions of the Royal Society A 379(2197), p.20200221 (link)
- Jansson, F., van den Oord, G., Pelupessy, I., Grönqvist, J.H., Siebesma, A.P. and Crommelin, D., 2019. Regional superparameterization in a global circulation model using large eddy simulations, Journal of Advances in Modeling Earth Systems 11(9), pp.2958-2979 (link)
- Bisewski, K., Crommelin, D. and Mandjes, M., 2019. Rare event simulation for steady-state probabilities via recurrency cycles, Chaos 29(3), p.033131 (link) (preprint)