| The ASHRAE great energy predictor III competition: Overview and results C Miller, P Arjunan, A Kathirgamanathan, C Fu, J Roth, JY Park, ... Science and Technology for the Built Environment 26 (10), 1427-1447, 2020 | 85 | 2020 |
| Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis C Miller, B Picchetti, C Fu, J Pantelic Science and Technology for the Built Environment 28 (5), 610-627, 2022 | 23 | 2022 |
| Using Google Trends as a proxy for occupant behavior to predict building energy consumption C Fu, C Miller Applied Energy 310, 118343, 2022 | 20 | 2022 |
| Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale H Kazmi, C Fu, C Miller Building and Environment 239, 110407, 2023 | 13 | 2023 |
| Gradient boosting machines and careful pre-processing work best: Ashrae great energy predictor iii lessons learned C Miller, L Hao, C Fu arXiv preprint arXiv:2202.02898, 2022 | 6 | 2022 |
| Filling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation C Fu, M Quintana, Z Nagy, C Miller Applied Thermal Engineering 236, 121545, 2024 | 5 | 2024 |
| Trimming outliers using trees: winning solution of the large-scale energy anomaly detection (LEAD) competition C Fu, P Arjunan, C Miller Proceedings of the 9th ACM International Conference on Systems for Energy …, 2022 | 5 | 2022 |
| Interpretable domain-informed and domain-agnostic features for supervised and unsupervised learning on building energy demand data A Canaydin, C Fu, A Balint, M Khalil, C Miller, H Kazmi Applied Energy 360, 122741, 2024 | 1 | 2024 |
| Enhancing Classification of Energy Meters with Limited Labels using a Semi-Supervised Generative Model C Fu, H Kazmi, M Quintana, C Miller Proceedings of the 10th ACM International Conference on Systems for Energy …, 2023 | 1 | 2023 |
| Opening the Black Box: Towards inherently interpretable energy data imputation models using building physics insight A Liguori, M Quintana, C Fu, C Miller, J Frisch, C van Treeck Energy and Buildings 310, 114071, 2024 | | 2024 |
| Creating synthetic energy meter data using conditional diffusion and building metadata C Fu, H Kazmi, M Quintana, C Miller arXiv preprint arXiv:2404.00525, 2024 | | 2024 |
| Introducing the Cool, Quiet City Competition: Predicting Smartwatch-Reported Heat and Noise with Digital Twin Metrics C Miller, M Quintana, M Frei, YX Chua, C Fu, B Picchetti, W Yap, A Chong, ... Proceedings of the 10th ACM International Conference on Systems for Energy …, 2023 | | 2023 |
| The Building Data Genome Directory–An open, comprehensive data sharing platform for building performance research X Jin, C Fu, H Kazmi, A Balint, A Canaydin, M Quintana, F Biljecki, F Xiao, ... Journal of Physics: Conference Series 2600 (3), 032003, 2023 | | 2023 |
Clayton MillerNational University of SingaporeVerified email at nus.edu.sg
