Science

New research evaluates how well artificial intelligence can anticipate security vulnerabilities based on bug reports.

New research details a novel approach to building more resilient stablecoin systems using collaborative, trust-weighted data aggregation.

A new approach dynamically adjusts regularization to improve the accuracy and robustness of time series predictions.

Researchers have developed a novel method to forecast how cells will respond to genetic or environmental changes, leveraging learned patterns from existing data.

Researchers have proposed a generalized loss function rooted in pattern correlation that aims to improve training across both traditional Support Vector Machines and modern Deep Neural Networks.

Researchers have developed a novel framework that leverages semantic topology learning to improve air quality predictions worldwide, even in areas with limited data.

A new approach to training complex AI models overcomes the challenges of vanishing and exploding gradients by propagating updates through textual representations.

New research demonstrates that the initial noise used in image generation models can reveal whether a specific image was part of their training dataset.

New research reveals that advanced artificial intelligence consistently outperforms humans in resisting emotional manipulation when making logical decisions under pressure.

Researchers have developed a novel framework that blends physics-based modeling with advanced machine learning to anticipate equipment failures with improved accuracy and reliability.