Abstract
We report on the use of a single, unified dataset for machine learning (ML)-driven solubility prediction across the chemical space. This was a departure from the solvent-specific datasets more commonly used.
Original language | English |
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Pages | 24-24 |
Number of pages | 1 |
Publication status | Published - 16 May 2022 |
Event | CMAC Annual Open Day 2022 - Glasgow, United Kingdom Duration: 16 May 2022 → 18 May 2022 |
Conference
Conference | CMAC Annual Open Day 2022 |
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Country/Territory | United Kingdom |
City | Glasgow |
Period | 16/05/22 → 18/05/22 |
Keywords
- machine learning
- solubility predication
- Conductor like Screening Model for Real Solvents (COSMO-RS)