Chemical property prediction under experimental biases
Abstract Predicting the chemical properties of compounds is crucial in discovering novel materials and drugs with specific desired characteristics. Recent significant advances in machine learning technologies have enabled automatic predictive modeling from past experimental data reported in the lite...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-12116-5 |