11 citations as recorded by crossref.

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4. Uncertainty quantification in water quality prediction using Optuna-optimized machine learning: A case study in the Quan Lo-Phung Hiep irrigation system, Vietnamese Mekong Delta H. Thi et al. https://doi.org/10.1016/j.jwpe.2026.109858
5. Kriging prior regression: A case for kriging-based spatial features with TabPFN in soil mapping J. Schmidinger et al. https://doi.org/10.1016/j.compag.2025.111352
6. Modern Neural Networks for Small Tabular Datasets: The New Default for Field‐Scale Digital Soil Mapping? V. Barkov et al. https://doi.org/10.1111/ejss.70299
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9. Mapping soil carbon content in two contrasting pedoclimatic regions using a deep learning approach with remote sensing imagery and laboratory spectral datasets H. Zayani et al. https://doi.org/10.1016/j.geoderma.2025.117513
10. Enhancing Influenza-Like Illness forecasting: An ensemble approach combining mathematical and deep learning models amidst the COVID-19 pandemic G. Yoon et al. https://doi.org/10.1016/j.epidem.2026.100901
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