| Assessment of the urban heat island in the city of Tehran using reliability methods MS Jahangir, S Moghim Atmospheric Research 225, 144-156, 2019 | 33 | 2019 |
| A quantile-based encoder-decoder framework for multi-step ahead runoff forecasting MS Jahangir, J You, J Quilty Journal of Hydrology 619, 129269, 2023 | 30 | 2023 |
| Influence of aquifer heterogeneity on sea level rise-induced seawater intrusion: A probabilistic approach H Ketabchi, MS Jahangir Journal of Contaminant Hydrology 236, 103753, 2021 | 20 | 2021 |
| Investigating the impact of input variable selection on daily solar radiation prediction accuracy using data-driven models: a case study in northern Iran MS Jahangir, SM Biazar, D Hah, J Quilty, M Isazadeh Stochastic Environmental Research and Risk Assessment 36 (1), 225-249, 2022 | 11 | 2022 |
| Probabilistic numerical assessment of seawater intrusion overshoot in heterogeneous coastal aquifers H Ketabchi, MS Jahangir Stochastic Environmental Research and Risk Assessment 33 (11), 1951-1968, 2019 | 11 | 2019 |
| Generative deep learning for probabilistic streamflow forecasting: Conditional variational auto-encoder MS Jahangir, J Quilty Journal of Hydrology 629, 130498, 2024 | 8 | 2024 |
| Bayesian extreme learning machines for hydrological prediction uncertainty J Quilty, MS Jahangir, J You, H Hughes, D Hah, I Tzoganakis Journal of Hydrology 626, 130138, 2023 | 7 | 2023 |
| Temporal hierarchical reconciliation for consistent water resources forecasting across multiple timescales: An application to precipitation forecasting MS Jahangir, J Quilty Water Resources Research 58 (6), e2021WR031862, 2022 | 4 | 2022 |
| Reliability framework for characterizing heat wave and cold spell events S Moghim, MS Jahangir Natural Hazards 112 (2), 1503-1525, 2022 | 3 | 2022 |
| A novel hybrid transfer-learning method to supercharge deep learning model development for hydrological prediction MS Jahangir, B Khalil, J Harms, J Quilty, A Scott, JF Adamowski AGU24, 2024 | | 2024 |
| Deep Learning-Based Probabilistic Hierarchical Reconciliation for Hydrological and Water Resources Forecasting MS Jahangir University of Waterloo, 2024 | | 2024 |
| Sequence-to-Sequence Deep Learning for Urban Water Demand Forecasting MS Jahangir, J Quilty Engineering Proceedings 69 (1), 41, 2024 | | 2024 |
| An ensemble deep learning approach to spatiotemporal tropospheric ozone forecasting: A case study of Tehran, Iran M Rezaali, MS Jahangir, R Fouladi-Fard, D Keellings Urban Climate 55, 101950, 2024 | | 2024 |
| Letting neural networks talk: exploring two probabilistic neural network models for input variable selection J Quilty, M Sina Jahangir EGU General Assembly Conference Abstracts, 4238, 2024 | | 2024 |
| Probabilistic streamflow forecasting using generative deep learning models MS Jahangir, J Quilty EGU24, 2024 | | 2024 |
| Deep Graph Neural Networks for Spatiotemporal Forecasting of Sub-Seasonal Sea Ice: A Case Study in Hudson Bay Z Gousseau, KA Scott, P Lamontagne, MS Jahangir Authorea Preprints, 2023 | | 2023 |
| Quantile-Based Encoder-Decoder Deep Learning Models for Multi-Step Ahead Hydrological Forecasting MS Jahangir, J You, J Quilty AGU Fall Meeting Abstracts 2022, H31E-07, 2022 | | 2022 |
| Quantifying Uncertainty in Hydrological Simulations and Forecasts using Bayesian and Sparse Bayesian Extreme Learning Machine Models MS Jahangir, J Quilty, J You, D Hah, H Hughes AGU Fall Meeting Abstracts 2022, H11E-03, 2022 | | 2022 |
| Improving hydrological forecasts through temporal hierarchal reconciliation MS Jahangir, J Quilty EGU21, 2021 | | 2021 |
| Remotely-Sensed Assessment of Water Stress in the Lake Urmia Basin MS Jahangir, M Javadian, M Abdoli, M Danesh-Yazdi, M Tajrishy AGU Fall Meeting Abstracts 2019, H31L-1894, 2019 | | 2019 |
John QuiltyUniversity of WaterlooVerified email at uwaterloo.ca