Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization
Abstract Neural processes (NPs) are models for meta-learning which output uncertainty estimates. So far, most studies of NPs have focused on low-dimensional datasets of highly-correlated tasks. While these homogeneous datasets are useful for benchmarking, they may not be representative of realistic...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-10-01
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| Series: | Journal of Cheminformatics |
| Online Access: | https://doi.org/10.1186/s13321-024-00904-2 |
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