Abstract: This review article addresses the problem of learning abstract representations of measurement data in the context of deep reinforcement learning. While the data are often ambiguous, ...

Awurum, N.P. (2025) Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience. Open Access Library Journal, 12, 1-17. doi: 10.4236/oalib.1114210 .

Explore the top 7 data science programs for business leaders in 2025. Learn which executive courses combine analytics, ...

Introduction: Myocardial ischemia can result in severe cardiovascular complications. However, the impact of clinical factors on myocardial ischemia in individuals with T2DM remains unclear. we applied ...

Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

Traditional cardiovascular risk assessment entails investigator‐defined exposure levels and individual risk markers in multivariable analysis. We sought to determine whether an alternative unbiased ...

TwinHead-RL is a research project on curiosity-driven deep RL. We use a multi-head agent that learns both policy and future state prediction, using prediction error ...

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...

This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...