A hydrologic functional approach for improving largesample hydrology performance in poorly gauged regions J Janssen, AA Ameli Water Resources Research 57 (9), e2021WR030263, 2021 | 13 | 2021 |
Assessment of Future Risks of Seasonal Municipal Water Shortages Across North America J Janssen, V Radić, A Ameli Frontiers in Earth Science 9, 730631, 2021 | 9 | 2021 |
Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees J Janssen, V Guan, E Robeva Proceedings of The 26th International Conference on Artificial Intelligence …, 2022 | 8* | 2022 |
The persistence of snow on the ground affects the shape of streamflow hydrographs over space and time: a continental-scale analysis E Le, J Janssen, J Hammond, AA Ameli Frontiers in Environmental Science 11, 1207508, 2023 | 5* | 2023 |
How to out-perform default random forest regression: choosing hyperparameters for applications in large-sample hydrology DK Bilolikar, A More, A Gong, J Janssen arXiv preprint arXiv:2305.07136, 2023 | 1 | 2023 |
Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science J Janssen, S Meng, A Haris, S Schrunner, J Cao, WJ Welch, N Kunz, ... arXiv preprint arXiv:2303.06501, 2023 | 1 | 2023 |
A critical appraisal of water table depth estimation: Challenges and opportunities within machine learning J Janssen, A Tootchi, AA Ameli arXiv preprint arXiv:2405.04579, 2024 | | 2024 |
A Gaussian Sliding Windows Regression Model for Hydrological Inference S Schrunner, J Janssen, A Jenul, J Cao, AA Ameli, WJ Welch arXiv preprint arXiv:2306.00453, 2023 | | 2023 |