A new active-inference account reframes attachment styles as calibrated models of the world—with consequences for how we ...

Utilities and power generation companies are bolstering operational efficiency and plant reliability by implementing advanced ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted consumer data. By combining ...

Cardiovascular diseases remain a leading cause of mortality globally, driving the need for more precise diagnostic and predictive tools. Traditional ...

BackgroundBird populations are facing unprecedented global pressures from climate change, habitat fragmentation, land use ...

TAR 2.0 is likely the most widely used analytic technology for reviewing large document collections for production (although ...

A forecasting framework that measures how voters evaluate candidates’ future leadership abilities and policy expertise accurately anticipated the closely contested outcome of the 2024 United States ...

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

Honeywell’s HALO machine learning system predicted pressure disturbances and cycle delays with 12-minute notice, enabling operators to take preventive action before shutdowns occurred. The ...

Functional connectivity (FC) analysis holds strong potential for predicting behavioral traits. However, whole-brain predictive models face challenges with interpretability and generalizability, while ...