Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets
With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of confidence to the model predictions naturally arises. Several methods for obtaining uncertainty estimates have been proposed in recent years but consensus on the evaluation...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing
2024
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| Online Access: | https://hdl.handle.net/1721.1/153303 |