Machine Learning
Superhard materials have recently attracted increasing research interest due to their potential implications for a broad range of industries
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Currently, manufacturers can only detect the quality and properties of graphene used in a product after it has been manufactured
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KAUST researchers have developed a machine learning model that can analyze the structure of hydrocarbon molecules and accurately predict a property called enthalpy of formation
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A new model improves how uncertainty is calculated when matching shoe print evidence, strengthening the validity of this forensics technique
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Researchers have developed an artificial intelligence-led process that uses big data to design new proteins
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New machine learning algorithm aims to make AI more energy efficient, solving a major hurdle in its broad use
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While deep learning is a very powerful tool, its use in genomics has been limited
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Complementary expertise provides a single vendor solution to streamline data workflows from ‘instrument to insight’, boosting research efficiency
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Researchers find that network simulations became unstable after continuous periods of unsupervised learning
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Backed by major pharma, the toolkit will improve data management and data sharing, supporting AI and machine learning to advance the lab of the future
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