Unravelling the interplay between hydrogen and grain boundary of α-Fe under different concentration and strain rate via neural network interatomic potential

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Trial launched to 'help spot health risks early'

One challenge is having enough training data. Another is that the training data needs to be free of contamination. For a model trained up till 1900, there needs to be no information from after 1900 that leaks into the data. Some metadata might have that kind of leakage. While it’s not possible to have zero leakage - there’s a shadow of the future on past data because what we store is a function of what we care about - it’s possible to have a very low level of leakage, sufficient for this to be interesting.。关于这个话题,爱思助手下载最新版本提供了深入分析