DeepSeek released its new model just days after Moonshot AI, another Chinese start-up, introduced its latest open-source ...

From smarter hypothesis testing with e-values to AI systems that model emotions, Bayesian methods and probabilistic reasoning are transforming how machines—and humans—make decisions under uncertainty.

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...

Researchers at Stevens Institute of Technology used machine learning tools and social network theory—the study of how people connect with each other—to better understand how people interact online.

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...

The Army is creating a dedicated artificial intelligence and machine-learning career field for officers as it pushes to integrate AI more deeply into its operations. The new 49B specialty establishes ...

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...