A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS) has developed a ...

Deep learning is increasingly being used to emulate cloud and convection processes in climate models, offering a faster ...

Scientists have developed an AI system that can rapidly predict complex defect patterns in liquid crystals, cutting simulation times from hours to milliseconds. The approach could transform how ...

Led by Professor Fu Jin, the study addresses a critical challenge in radiation therapy: balancing the computational speed and ...

AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

A new artificial intelligence approach combines deep learning with physical modeling to extract detailed aerosol properties from complex satellite observations. By learning how light intensity and ...

Abstract: The non-convexity of rate-splitting precoder design precludes the direct use of efficient convex optimization algorithms. Instead, successive convex approximation (SCA)-based methods have ...

An important but unresolved question in deep learning for EEG decoding is which features neural networks learn to solve the task. Prior interpretability studies have mainly explained individual ...

Max Delbrück Center for Molecular Medicine in the Helmholtz Association Altuna Akalin and his team at the Max Delbrück Center have developed a new tool to more precisely guide cancer treatment.