Physics-trained autoencoder tidies weather data but cannot beat raw inputs for evapotranspiration
A physics-regularized autoencoder cut dew-point inconsistency in reconstructed Delhi weather data by 87 percent, yet still could not beat XGBoost ...
A physics-regularized autoencoder cut dew-point inconsistency in reconstructed Delhi weather data by 87 percent, yet still could not beat XGBoost ...
A database analysis of 2073 UHPC mixtures from 165 publications finds that filler type and dosage have only small associations ...
Researchers report a simulation-based explainability framework that pairs a physics-guided reinforcement learning controller with XGBoost and SHAP analysis to trace ...
A graph neural network trained on about 2.1 million PanDA job records predicts job turnaround time with an R-squared of ...
A multicenter study combined CT-derived radiomic features with clinical data in an XGBoost model that predicted outcomes after aneurysmal subarachnoid ...
Researchers trained an XGBoost machine learning model to estimate the residual tensile strength of artificially aged silk textiles from nondestructive ...
Researchers in Cameroon built and tested a machine learning model that predicts antiretroviral resistance from routine clinical data, with XGBoost ...
A Nature Food study finds that Chinese wheat yields have become increasingly sensitive to compound hot–dry–windy events between 1981 and ...
A new GeoAI framework combining Google Earth Engine, ensemble machine learning, and SHAP explainability mapped landslide susceptibility across central Nepal ...
A condition-stratified study of westbound Interstate I-94 found that XGBoost without weather variables delivered the most accurate hour-ahead traffic forecasts.
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© 2026 Scienmag - Science Magazine