| Global wildfire susceptibility mapping based on machine learning models A Shmuel, E Heifetz Forests 13 (7), 1050, 2022 | 50 | 2022 |
| The political budget cycle across varying degrees of democracy A Shmuel Electoral Studies 68, 102218, 2020 | 21 | 2020 |
| Machine-Learning-based evaluation of the time-lagged effect of meteorological factors on 10-hour dead fuel moisture content A Shmuel, Y Ziv, E Heifetz Forest Ecology and Management 505, 119897, 2022 | 17 | 2022 |
| Developing novel machine-learning-based fire weather indices A Shmuel, E Heifetz Machine Learning: Science and Technology 4 (1), 015029, 2023 | 12 | 2023 |
| A machine-learning approach to predicting daily wildfire expansion rate A Shmuel, E Heifetz Fire 6 (8), 319, 2023 | 9 | 2023 |
| Symbolic regression as a feature engineering method for machine and deep learning regression tasks A Shmuel, O Glickman, T Lazebnik Machine Learning: Science and Technology 5 (2), 025065, 2024 | 4 | 2024 |
| Explaining the pre-election peace A Shmuel The British Journal of Politics and International Relations 23 (3), 488-512, 2021 | 3 | 2021 |
| A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets A Shmuel, O Glickman, T Lazebnik arXiv preprint arXiv:2408.14817, 2024 | 2 | 2024 |
| Re-examining the assumption of dominant regional wind and fire spread directions A Shmuel, E Heifetz International journal of wildland fire 31 (5), 480-491, 2022 | 2 | 2022 |
| Empirical evidence of reduced wildfire ignition risk in the presence of strong winds A Shmuel, E Heifetz Fire 6 (9), 338, 2023 | 1 | 2023 |
| Data Augmentation for Deep Learning Regression Tasks by Machine Learning Models A Shmuel, O Glickman, T Lazebnik arXiv preprint arXiv:2501.03654, 2025 | | 2025 |
| Machine and deep learning performance in out-of-distribution regressions A Shmuel, O Glickman, T Lazebnik Machine Learning: Science and Technology 5 (4), 045078, 2025 | | 2025 |
| The Consequences of Electoral Uncertainty in Foreign Policy-Making: The Use of Diversionary Sanctions A Shmuel International Journal 79 (4), 510-541, 2024 | | 2024 |
| Global Lightning-Ignited Wildfires Prediction and Climate Change Projections based on Explainable Machine Learning Models A Shmuel, T Lazebnik, O Glickman, E Heifetz, C Price arXiv preprint arXiv:2409.10046, 2024 | | 2024 |
| Lightning-Ignited Wildfires On A Global Scale: Prediction and Climate Change Projections based on Explainable Machine Learning Models A Shmuel, O Glickman, T Lazebnik, E Heifetz, C Price EMS2024, 2024 | | 2024 |
| A Dijkstra-based approach to fuelbreak planning A Shmuel, E Heifetz Fire 6 (8), 295, 2023 | | 2023 |
| Novel machine-learning-based fire weather indices A Shmuel, E Heifetz EMS2023, 2023 | | 2023 |
