| Bayesian estimates of parameter variability in the k–ε turbulence model WN Edeling, P Cinnella, RP Dwight, H Bijl Journal of Computational Physics 258, 73-94, 2014 | 249 | 2014 |
| Predictive RANS simulations via Bayesian model-scenario averaging WN Edeling, P Cinnella, RP Dwight Journal of Computational Physics 275, 65-91, 2014 | 139 | 2014 |
| The impact of uncertainty on predictions of the CovidSim epidemiological code W Edeling, H Arabnejad, R Sinclair, D Suleimenova, K Gopalakrishnan, ... Nature Computational Science 1 (2), 128-135, 2021 | 76 | 2021 |
| EasyVVUQ: a library for verification, validation and uncertainty quantification in high performance computing RA Richardson, DW Wright, W Edeling, V Jancauskas, J Lakhlili, ... Journal of open research software 8 (1), 2020 | 51 | 2020 |
| Data-free and data-driven RANS predictions with quantified uncertainty WN Edeling, G Iaccarino, P Cinnella Flow, Turbulence and Combustion 100, 593-616, 2018 | 47 | 2018 |
| Ensembles are required to handle aleatoric and parametric uncertainty in molecular dynamics simulation M Vassaux, S Wan, W Edeling, PV Coveney Journal of chemical theory and computation 17 (8), 5187-5197, 2021 | 40 | 2021 |
| Eigenvector perturbation methodology for uncertainty quantification of turbulence models RL Thompson, AA Mishra, G Iaccarino, W Edeling, L Sampaio Physical Review Fluids 4 (4), 044603, 2019 | 35 | 2019 |
| Building confidence in simulation: applications of EasyVVUQ DW Wright, RA Richardson, W Edeling, J Lakhlili, RC Sinclair, ... Advanced Theory and Simulations 3 (8), 1900246, 2020 | 33 | 2020 |
| Bayesian predictions of Reynolds-averaged Navier–Stokes uncertainties using maximum a posteriori estimates WN Edeling, M Schmelzer, RP Dwight, P Cinnella AIAA Journal 56 (5), 2018-2029, 2018 | 33 | 2018 |
| Simplex-stochastic collocation method with improved scalability WN Edeling, RP Dwight, P Cinnella Journal of Computational Physics 310, 301-328, 2016 | 30 | 2016 |
| VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations D Groen, H Arabnejad, V Jancauskas, WN Edeling, F Jansson, ... Philosophical Transactions of the Royal Society A 379 (2197), 20200221, 2021 | 24 | 2021 |
| Introducing vecmatk-verification, validation and uncertainty quantification for multiscale and hpc simulations D Groen, RA Richardson, DW Wright, V Jancauskas, R Sinclair, ... Computational Science–ICCS 2019: 19th International Conference, Faro …, 2019 | 20 | 2019 |
| Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model F Gugole, LE Coffeng, W Edeling, B Sanderse, SJ De Vlas, D Crommelin PLoS computational biology 17 (9), e1009355, 2021 | 17 | 2021 |
| Sensitivity-driven simulation development: a case study in forced migration D Suleimenova, H Arabnejad, WN Edeling, D Groen Philosophical Transactions of the Royal Society A 379 (2197), 20200077, 2021 | 17 | 2021 |
| Reducing data-driven dynamical subgrid scale models by physical constraints W Edeling, D Crommelin Computers & Fluids 201, 104470, 2020 | 16 | 2020 |
| Energy-conserving neural network for turbulence closure modeling T van Gastelen, W Edeling, B Sanderse Journal of Computational Physics 508, 113003, 2024 | 14 | 2024 |
| FabSim3: An automation toolkit for verified simulations using high performance computing D Groen, H Arabnejad, D Suleimenova, W Edeling, E Raffin, Y Xue, ... Computer Physics Communications 283, 108596, 2023 | 14 | 2023 |
| On the deep active-subspace method W Edeling SIAM/ASA Journal on Uncertainty Quantification 11 (1), 62-90, 2023 | 13 | 2023 |
| Uncertainty quantification patterns for multiscale models D Ye, L Veen, A Nikishova, J Lakhlili, W Edeling, OO Luk, ... Philosophical Transactions of the Royal Society A 379 (2197), 20200072, 2021 | 13 | 2021 |
| Resampling with neural networks for stochastic parameterization in multiscale systems D Crommelin, W Edeling Physica D: Nonlinear Phenomena 422, 132894, 2021 | 12 | 2021 |