Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for clean-energy reactions are screened, identified, and validated across ...
Abstract: Context: Ensemble methods are powerful machine learning algorithms that combine multiple models to enhance prediction capabilities and reduce generalization errors. However, their potential ...
Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...
This integration addresses the fundamental barriers that have historically limited formal verification adoption: complexity ...
Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
AI-powered spectral sensor performs machine learning during light capture, identifying materials and chemicals in real time ...
Abstract: Exponential growth of unstructured data in the form of text documents, emails, and web content presents a noticeable challenge to automated data extraction. This kind of data has much more ...
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