Deep learning (DL) is a modern powerful instrument for multiple purposes, including classification. In this study, this technique is applied to the task of perovskites formability. A commonly known perovskite dataset is used to try to make an instrument superior to the ‘classic’ geometric approach. The authors found that the resulting models allow the finding of inaccuracies in the data and can successfully forecast perovskite formability with an accuracy of over 98% for the best case.

中文翻译：

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超出公差因素：使用深度学习预测ABX3钙钛矿结构的可成形性

深度学习（DL）是一种现代强大的工具，可用于多种目的，包括分类。在这项研究中，此技术应用于钙钛矿的可成形性任务。使用通常已知的钙钛矿数据集来尝试使一种仪器优于“经典”几何方法。作者发现，所得模型可以发现数据中的不准确之处，并且在最佳情况下可以成功地预测钙钛矿的可成形性，其准确度超过98％。