Process‐based climate model development harnessing machine learning: I. A calibration tool for parameterization improvement F Couvreux, F Hourdin, D Williamson, R Roehrig, V Volodina, ... Journal of Advances in Modeling Earth Systems 13 (3), e2020MS002217, 2021 | 73 | 2021 |
The importance of uncertainty quantification in model reproducibility V Volodina, P Challenor Philosophical Transactions of the Royal Society A 379 (2197), 2021 | 50 | 2021 |
Process‐based climate model development harnessing machine learning: II. Model calibration from single column to global F Hourdin, D Williamson, C Rio, F Couvreux, R Roehrig, N Villefranque, ... Journal of Advances in Modeling Earth Systems 13 (6), e2020MS002225, 2021 | 47 | 2021 |
Diagnostics-driven nonstationary emulators using kernel mixtures V Volodina, D Williamson SIAM/ASA Journal on Uncertainty Quantification 8 (1), 1-26, 2020 | 24 | 2020 |
Process‐based climate model development harnessing machine learning: III. The representation of cumulus geometry and their 3D radiative effects N Villefranque, S Blanco, F Couvreux, R Fournier, J Gautrais, RJ Hogan, ... Journal of Advances in Modeling Earth Systems 13 (4), e2020MS002423, 2021 | 14 | 2021 |
Comparing district heating options under uncertainty using stochastic ordering V Volodina, E Wheatcroft, H Wynn Sustainable Energy, Girds and Networks, 2022 | 12* | 2022 |
Process-based climate model development harnessing machine learning: II. Model calibration from single column to global F Hourdin, D Williamson, C Rio, F Couvreux, R Roehrig, N Villefranque, ... Authorea Preprints, 2022 | 6 | 2022 |
Villefranque, 522 N.,... others (2021). Process-based climate model development harnessing 523 machine learning: I. A calibration tool for parameterization improvement. J. 524 … F Couvreux, F Hourdin, D Williamson, R Roehrig, V Volodina Earth Sys 13, e2020MS002217, 0 | 6 | |
Process-based climate model development harnessing machine learning: III. The Representation of Cumulus Geometry and their 3D Radiative Effects N Villefranque, D Williamson, F Couvreux, F Hourdin, J Gautrais, ... Authorea Preprints, 2022 | 4 | 2022 |
Model-based contract design for low energy waste heat contracts: the route to pricing E Wheatcroft, HP Wynn, V Volodina, CJ Dent, K Lygnerud Energies 14 (12), 3614, 2021 | 4 | 2021 |
Propagating uncertainty in a network of energy models V Volodina, N Sonenberg, JQ Smith, PG Challenor, CJ Dent, HP Wynn 2022 17th International Conference on Probabilistic Methods Applied to Power …, 2022 | 3 | 2022 |
Using infinite server queues with partial information for occupancy prediction N Sonenberg, V Volodina, PG Challenor, JQ Smith Journal of the Operational Research Society 75 (2), 262-277, 2024 | 2 | 2024 |
SECRET: Statistical Emulation for Computational Reverse Engineering and Translation with applications in healthcare LM Paun, MJ Colebank, A Taylor-LaPole, MS Olufsen, W Ryan, I Murray, ... Computer Methods in Applied Mechanics and Engineering 430, 117193, 2024 | 1 | 2024 |
Uncertainty Quantification for complex computer models with nonstationary output. Bayesian optimal design for iterative refocussing V Volodina PQDT-UK & Ireland, 2019 | 1 | 2019 |
Challenges and opportunities in uncertainty quantification for healthcare and biological systems LM Kimpton, LM Paun, MJ Colebank, V Volodina Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2024 | | 2024 |
Propagating moments in probabilistic graphical models for decision support systems V Volodina, N Sonenberg, P Challenor, JQ Smith arXiv preprint arXiv:2312.03643, 2023 | | 2023 |
A Bayesian Decision Support System in Energy Systems Planning V Volodina, N Sonenberg, P Challenor, J Smith https://arxiv.org/abs/2204.05035, 2022 | | 2022 |
Majorization as a theory for uncertainty V Volodina, N Sonenberg, E Wheatcroft, H Wynn International Journal for Uncertainty Quantification 12 (5), 2022 | | 2022 |
An integrating decision support system in energy systems planning V Volodina, N Sonenberg, J Smith, C Dent, H Wynn | | 2021 |