Interpretable Fragment‐Based Molecule Design with Self‐Learning Entropic Population Annealing
Self‐learning entropic population annealing (SLEPA) is a recently developed method used for achieving interpretable black‐box optimization via density‐of‐states estimation. Applying SLEPA to a chemical space is not straightforward, however, because of its dependence on Markov chain Monte Carlo sampl...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-10-01
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| Series: | Advanced Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/aisy.202300189 |