Geometric deep learning for molecular property predictions with chemical accuracy across chemical space
Abstract Chemical engineers heavily rely on precise knowledge of physicochemical properties to model chemical processes. Despite the growing popularity of deep learning, it is only rarely applied for property prediction due to data scarcity and limited accuracy for compounds in industrially-relevant...
I tiakina i:
| Ngā kaituhi matua: | , , , |
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| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
BMC
2024-08-01
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| Rangatū: | Journal of Cheminformatics |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1186/s13321-024-00895-0 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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