Find the best datasets for intermediate fine-tuning
Predict how well a transfer-learning dataset will work before fine-tuning on it. TLDChoiceNet cuts prediction MSE 5x, and an unsupervised class-correlation metric explains fine-tune accuracy with R2=0.97. Stanford CS 330.
Code and data repository for selection of datasets for FAIRification in Drug Discovery and Development.
Official minimal release for LED: dataset scoring and compact data subset selection.
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