Microsoft's Phi-4-reasoning-vision-15B uses careful data curation and selective reasoning to compete with models trained on ...

Abstract: The growth of frequency bandwidths in the new generation of wireless networks gives rise to the multitude of wireless communication scenarios and highlights the challenges of generalized ...

Abstract: Sparse Bayesian learning (SBL) is an algorithm for high-dimensional data processing based on Bayesian statistical theory. Its goal is to improve the generalization ability and efficiency of ...

A study published in The Journal of Engineering Research (TJER) at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...

This study provides important insights into how working memory shapes perceptual decisions, using a dual-task design, continuous mouse tracking, and hierarchical Bayesian modeling. By dissociating ...

Japan is an archipelago with diverse climate zones and complex topography that is prone to heavy rain and flooding. Add the ...

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Today, most investment firms use AI to assist human managers, providing data or suggestions for them to act on. BAILA represents a new category of AI-Managed Investing, where the AI makes the ...

Bayesian statistical models could help address recruitment challenges, but experts agree that sponsors must first understand – and be prepared - for the additional work required to implement them ...

New deep-learning framework reconstructs hourly PM2.5 chemical composition using air-quality and meteorological data ...

Probabilistic analysis of Brent oil prices using Bayesian change point detection to identify structural breaks and their association with major geopolitical and economic events. This project features ...