Science

New research reveals consistent patterns of financial network reorganization during the pandemic, indicating heightened systemic risk and lingering vulnerabilities across global economies.

A new review challenges the assumption that artificial intelligence automatically improves regional climate projections, suggesting established methods remain competitive and crucial for reliable future assessments.

A new deep learning model analyzes full-day electrocardiograms to forecast heart failure risk up to five years before traditional diagnosis.

A new physics-informed machine learning approach is unlocking the secrets of iron’s behavior at the extreme temperatures and pressures of Earth’s core.

A new framework leverages neural networks and advanced mathematical techniques to efficiently predict the behavior of complex plasmas under uncertainty.

New research explores how to imbue AI agents with the ability to understand sarcasm, moving past simple keyword detection towards true contextual reasoning.

A new machine learning approach accurately reconstructs how light echoes within active galaxies, revealing crucial information about their central engines.

A new control framework enables heterogeneous multi-agent systems to maintain coordinated behavior even with significant communication delays.

As network conditions evolve, maintaining accurate traffic classification requires continuous adaptation and a robust understanding of underlying data stability.

Researchers have developed a novel compression technique that preserves the critical spectral details in high-resolution solar imagery, enabling more efficient storage and analysis of this valuable data.