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Retrieved on: 2025-02-10 08:56:32
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Summary
The article discusses how researchers at Kyoto University use Generative Adversarial Networks (GANs) and ensemble learning, including message-passing neural networks, to improve the prediction of semiconductor band gaps. The approach ties into machine learning and computational statistics, enhancing accuracy and efficiency in material characterization.
Article found on: www.miragenews.com
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