A new approach to semi-decentralized spatio-temporal graph neural networks intelligently reduces communication overhead without sacrificing prediction quality, especially during critical traffic incidents.
A new analysis digs into the complex causal factors that can lead to AI systems operating outside of intended parameters.
Researchers have released a comprehensive aerial imagery dataset designed to help artificial intelligence better understand and respond to flooded environments.
As vehicles gain more autonomy through artificial intelligence, a new landscape of cybersecurity threats emerges, demanding proactive analysis and mitigation.
New research explores how conversational artificial intelligence, powered by large language models, is being developed to provide early and accurate medical diagnoses.
A new framework uses network analysis to detect hidden vulnerabilities in financial systems before they trigger widespread crashes.
Researchers have developed a novel AI model that leverages causal reasoning and domain adaptation to more accurately classify infant cries and improve understanding of a baby’s needs.
New research reveals that the mistakes made by artificial intelligence aren’t simply bugs, but stem from a human tendency to prioritize compelling narratives over verifiable facts.
A new deep learning framework leverages causal discovery to improve the accuracy and interpretability of streamflow forecasting, particularly for long-range predictions.
Researchers have developed a new framework for understanding and controlling the inner workings of neural networks, allowing for precise, quantifiable manipulation of their behavior.