A physics-inspired approach to the understanding of molecular representations and models
The story of machine learning in general, and its application to molecular design in particular, has been a tale of evolving representations of data. Understanding the implications of the use of a particular representation – including the existence of so-called ‘activity cliffs’ for cheminformatics...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Royal Society of Chemistry
2025
|
| Online Access: | https://hdl.handle.net/1721.1/158177 |