Science

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.

A new framework leverages large language models to unify control and reasoning across radio access and core networks, promising more adaptable and efficient future networks.

Researchers have developed a method to distill complex neural networks into simpler, more understandable models by actively testing and removing redundant components.

A new framework combines the strengths of statistical learning and symbolic reasoning to move medical AI beyond simple prediction and towards robust, interpretable decision support.