Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Structural economic models, while parsimonious and interpretable, often exhibit poor data fit and limited forecasting performance. Machine learning models, by contrast, offer substantial flexibility ...
Researchers at University of Toronto Engineering, led by Professor Yu Zou, are leveraging machine learning to improve additive manufacturing, also commonly known as 3D printing. In a new paper, ...
Cambodia is not alone in facing capacity limitations in the production and timely release of key official statistics needed for data-driven policy decisions. This paper demonstrates that combining ...
Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...
By leveraging AI/ML-driven modeling, Keysight enables semiconductor companies to accelerate innovation, reduce development ...
"The machine learning AFM framework provides a powerful atomic-scale tool to investigate disordered interfaces, phase transitions, and material defects, with broad potential applications in catalytic ...
A new research paper shows the approach performs significantly better than the random-walk forecasting method.
TrialTranslator uncovers the survival gap for high-risk patients and offers a path to better cancer research. Study: Evaluating generalizability of oncology trial results to real-world patients using ...
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