| Pdebench: An extensive benchmark for scientific machine learning M Takamoto, T Praditia, R Leiteritz, D MacKinlay, F Alesiani, D Pflüger, ... Advances in Neural Information Processing Systems 35, 1596-1611, 2022 | 105 | 2022 |
| Fast and accurate computation of the distribution of sums of dependent log-normals ZI Botev, R Salomone, D Mackinlay Annals of Operations Research 280, 19-46, 2019 | 10 | 2019 |
| Bayesian physics informed neural networks for data assimilation and spatio-temporal modelling of wildfires JJ Dabrowski, DE Pagendam, J Hilton, C Sanderson, D MacKinlay, ... Spatial Statistics 55, 100746, 2023 | 9 | 2023 |
| Accurate computation of the distribution of sums of dependent log-normals with applications to the Black-Scholes model Z Botev, R Salomone, D Mackinlay arXiv preprint arXiv:1705.03196, 2017 | 9 | 2017 |
| A universal splitting estimator for the performance evaluation of wireless communications systems NB Rached, D MacKinlay, Z Botev, R Tempone, MS Alouini IEEE Transactions on Wireless Communications 19 (7), 4353-4362, 2020 | 5 | 2020 |
| A log-additive neural model for spatio-temporal prediction of groundwater levels D Pagendam, S Janardhanan, J Dabrowski, D MacKinlay Spatial Statistics 55, 100740, 2023 | 4 | 2023 |
| Model Inversion for Spatio-temporal Processes using the Fourier Neural Operator D MacKinlay, D Pagendam, PM Kuhnert, T Cui, D Robertson, ... Neurips Workshop on Machine Learning for the Physical Sciences, 7, 2021 | 3 | 2021 |
| Logarithmically efficient estimation of the tail of the multivariate normal distribution Z Botev, D Mackinlay, YL Chen 2017 Winter Simulation Conference (WSC), 1903-1913, 2017 | 3 | 2017 |
| Mosaic Style Transfer Using Sparse Autocorrelograms D MacKinlay, ZI Botev Proceedings of the Congress of International Society for Music Information …, 2019 | 1 | 2019 |
| Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems D MacKinlay, R Tsuchida, D Pagendam, P Kuhnert arXiv preprint arXiv:2402.08193, 2024 | | 2024 |
| Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires J Janek Dabrowski, DE Pagendam, J Hilton, C Sanderson, D MacKinlay, ... arXiv e-prints, arXiv: 2212.00970, 2022 | | 2022 |
| Groundwater balance estimators using Machine Learning S Janardhanan, D Pagendam, D MacKinlay, J Pena-Arancibia, ... EGU General Assembly Conference Abstracts, EGU22-8976, 2022 | | 2022 |
| Essays in simulation and stochastic processes D Mackinlay UNSW Sydney, 2021 | | 2021 |
| Iterative Nonlinear Self-Interference Cancellation for In-Band Full-Duplex Wireless Communications Under Mixer Imbalance and Amplifier Nonlinearity … NB Rached, D Mackinlay, Z Botev, R Tempone, MS Alouini, E Gruppi, ... | | |
Robert SalomoneQueensland University of TechnologyVerified email at qut.edu.au
