| Monash time series forecasting archive R Godahewa, C Bergmeir, GI Webb, RJ Hyndman, P Montero-Manso Neural Information Processing Systems (NeurIPS) - Datasets and Benchmarks Track, 2021 | 184 | 2021 |
| Ensembles of localised models for time series forecasting R Godahewa, K Bandara, GI Webb, S Smyl, C Bergmeir Knowledge-Based Systems 233, 107518, 2021 | 48 | 2021 |
| Association between urine output and mortality in critically ill patients: a machine learning approach AJ Heffernan, S Judge, SM Petrie, R Godahewa, C Bergmeir, D Pilcher, ... Critical care medicine 50 (3), e263-e271, 2022 | 19 | 2022 |
| Handling concept drift in global time series forecasting Z Liu, R Godahewa, K Bandara, C Bergmeir Forecasting with Artificial Intelligence: Theory and Applications, 163-189, 2023 | 12 | 2023 |
| A generative deep learning framework across time series to optimize the energy consumption of air conditioning systems R Godahewa, C Deng, A Prouzeau, C Bergmeir IEEE Access 10, 6842-6855, 2022 | 12 | 2022 |
| An accurate and fully-automated ensemble model for weekly time series forecasting R Godahewa, C Bergmeir, GI Webb, P Montero-Manso International Journal of Forecasting 39 (2), 641-658, 2023 | 11 | 2023 |
| Simulation and optimisation of air conditioning systems using machine learning R Godahewa, C Deng, A Prouzeau, C Bergmeir arXiv preprint arXiv:2006.15296, 2020 | 11 | 2020 |
| A strong baseline for weekly time series forecasting R Godahewa, C Bergmeir, GI Webb, P Montero-Manso arXiv preprint arXiv:2010.08158, 2020 | 9 | 2020 |
| SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting R Godahewa, GI Webb, D Schmidt, C Bergmeir Machine Learning 112 (7), 2555-2591, 2023 | 7 | 2023 |
| Comparison and evaluation of methods for a predict+ optimize problem in renewable energy C Bergmeir, F de Nijs, A Sriramulu, M Abolghasemi, R Bean, J Betts, ... arXiv preprint arXiv:2212.10723, 2022 | 7 | 2022 |
| A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition K Bandara, H Hewamalage, R Godahewa, P Gamakumara International Journal of Forecasting 38 (4), 1400-1404, 2022 | 7 | 2022 |
| Ieee-cis technical challenge on predict+ optimize for renewable energy scheduling C Bergmeir, F de Nijs, S Ferraro, L Magdalena, P Stuckey, Q Bui, ... URL: https://dx. doi. org/10.21227/1x9c-0161, doi 10, 2021 | 7 | 2021 |
| Seasonal averaged one-dependence estimators: a novel algorithm to address seasonal concept drift in high-dimensional stream classification R Godahewa, T Yann, C Bergmeir, F Petitjean 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 3 | 2020 |
| On Forecast Stability R Godahewa, C Bergmeir, ZE Baz, C Zhu, Z Song, S García, D Benavides arXiv preprint arXiv:2310.17332, 2023 | 2 | 2023 |
| Forecasting with Artificial Intelligence: Theory and Applications M Hamoudia, S Makridakis, E Spiliotis Springer Nature, 2023 | 2 | 2023 |
| Scalable probabilistic forecasting in retail with gradient boosted trees: A practitioner’s approach X Long, Q Bui, G Oktavian, DF Schmidt, C Bergmeir, R Godahewa, ... International Journal of Production Economics 279, 109449, 2025 | | 2025 |
| The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond D Pekaslan, JM Alonso-Moral, K Bandara, C Bergmeir, ... arXiv preprint arXiv:2311.04007, 2023 | | 2023 |
| Short-term traffic prediction with visitor location registry data F Dilhasha, K Fernando, R Godahewa, S Ossen, AS Perara, M Walpola Engineering Research Unit, Faculty of Engiennring, University of Moratuwa, 2016 | | 2016 |
| Short-Term Traffic Prediction Using Visitor Location Registry Data S Ossen, K Fernando, R Godahewa, F Dilhasha, AS Perera, M Walpola | | |
| Improving the Accuracy of Time Series Forecasting with Global Modelling and Ensembling RW GODAHEWA Monash University, 0 | | |