Active learning.

<p>(A) Schematic of active learning approach. A model is trained on an initial dataset, and is then retrained in each iteration by adding more points to the training set based on some selection criteria. (B-D) Uncertainty-guided active learning in protein sequence-function prediction. Spearman...

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Bibliographic Details
Main Author:	Kevin P. Greenman (17703253) (author)
Other Authors:	Ava P. Amini (15853140) (author), Kevin K. Yang (4528963) (author)
Published:	2025
Subjects:	Biochemistry Cell Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified select new sequences require calibrated estimations fitness landscape inference benchmarks enable us outperform greedy sampling metrics using one benchmarking uncertainty quantification retrospective active learning bayesian optimization settings bayesian optimization active learning based sampling property optimization results indicate results extend regression tasks rank correlation provide recommendations protein engineering often unable molecular machine model uncertainty model improvement learning datasets hot encoding function models effective design
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Active learning.

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