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 ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Researchers at Chungnam National University have developed a deep learning method that predicts stable defect configurations in nematic liquid crystals in milliseconds rather than hours. This rapid ...

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...

Lifelong plasticity is a core principle of neuroscience, yet it operates within real limits shaped by effort, stress and ...

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry transitions into an ordered ...

Recent research (2024-2025) consistently demonstrates the advantages of integrated AI-VR training: Knowledge Acquisition: ...

Order doesn’t always form perfectly—and those imperfections can be surprisingly powerful. In materials like liquid crystals, ...