Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends and to the robotics systems powering automation. They're also inside more ...
Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...
Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...
Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the ...
US-DATA, a data annotation company specializing in machine learning and computer vision projects, announces the expansion of ...
The ECB recalibrated its economic models with AI and machine learning, forecasting 3.0% inflation and 0.8% GDP growth for ...
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