Science

A new framework leverages multi-agent systems and causal reasoning to better identify individuals at risk of suicide based on their online conversations.

A new approach leverages the power of graph neural networks to analyze whole-slide images and predict patient survival rates with improved accuracy.

A new approach leverages convolutional neural networks to significantly speed up the complex process of gauge fixing in lattice quantum chromodynamics.

Researchers have developed a new method combining neural networks with ensemble Kalman filtering to significantly improve the accuracy and stability of simulations involving compressible flows with shocks.

New research reveals a method for converting weighted automata into equivalent probabilistic models, bridging a gap between these formalisms and offering a unified approach to analysis.

A new data-driven approach forecasts high-impedance arc faults in medium-voltage distribution systems, potentially preventing costly outages and improving grid reliability.

As organizations grapple with increasingly complex and interconnected crises, generative artificial intelligence offers a surprising path to innovation by repurposing existing knowledge assets.

Researchers have developed a system using artificial intelligence to proactively investigate and map the infrastructure behind increasingly sophisticated job scam operations.

New research reveals that negative spillover effects ripple through the cryptocurrency ecosystem, impacting assets across different blockchains as investors shift capital in response to market downturns.

As artificial intelligence increasingly integrates with critical infrastructure, a holistic, lifecycle-based security approach is essential to mitigate emerging threats.