摘要
A proof-of-concept methodology for addressing small amounts of chemical data using transfer learning is presented. We demonstrate this by applying transfer learning combined with the transformer model to small-dataset Heck reaction prediction. Introducing transfer learning significantly improved the accuracy of the transformer-transfer learning model (94.9%) over that of the transformer-baseline model (66.3%).
原文 | English |
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頁(從 - 到) | 9368-9371 |
頁數 | 4 |
期刊 | Chemical Communications |
卷 | 56 |
發行號 | 65 |
DOIs | |
出版狀態 | Published - 21 8月 2020 |
對外發佈 | 是 |