Science

Researchers have developed a machine learning tool to efficiently identify rare and unusual events in vast amounts of solar observation data, promising new discoveries in solar physics.

New research reveals that despite being designed for long-range interactions, Graph Transformers can actually worsen bottlenecks in graph data, hindering their ability to capture global relationships.

As artificial intelligence gains true autonomy, establishing clear rules for ownership is critical to fostering innovation and ensuring accountability.

This review examines the latest advances in artificial intelligence designed to identify and mitigate the spread of hateful content on social media platforms.

New research links the fundamental question of computational complexity-whether problems verifiable in polynomial time are also solvable in polynomial time-to the very sustainability of competitive market dynamics.

A new statistical framework reveals how narratives evolve within large collections of text over time.

New research confirms a theoretical link between the distribution of trade sizes and the long-term patterns observed in financial markets.

A new approach to federated learning enables banks and institutions to collaboratively build powerful fraud detection models without sharing sensitive customer data.

A new survey traces the evolution of meta-learning and meta-reinforcement learning, revealing the path towards truly adaptable artificial intelligence.

A new framework leverages reinforcement learning to optimize both electricity market bidding strategies and long-term transmission network expansion.