| Gaussian process emulation of spatio-temporal outputs of a 2D inland flood model J Donnelly, S Abolfathi, J Pearson, O Chatrabgoun, A Daneshkhah Water Research 225, 119100, 2022 | 86 | 2022 |
| Forecasting global climate drivers using Gaussian processes and convolutional autoencoders J Donnelly, A Daneshkhah, S Abolfathi Engineering Applications of Artificial Intelligence 128, 107536, 2024 | 46 | 2024 |
| Physics-informed neural networks as surrogate models of hydrodynamic simulators J Donnelly, A Daneshkhah, S Abolfathi Science of the Total Environment 912, 168814, 2024 | 39 | 2024 |
| A physics-informed neural network surrogate model for tidal simulations J Donnelly, S Abolfathi, A Daneshkhah ECCOMAS Proceedia, 836-844, 2023 | 9 | 2023 |
| Physics-Informed Neural Networks for Statistical Emulation of Hydrodynamical Numerical Models J Donnelly, A Daneshkhah, S Abolfathi EGU General Assembly Conference Abstracts, EGU-5445, 2023 | | 2023 |
