Transfer learning enables the transfer of knowledge gained while learning to perform one task (source) to a related but different task (target), hence addressing the expense of data acquisition and ...

While LC retention time prediction of peptides and their modifications has proven useful, widespread adoption and optimal performance are hindered by variations in experimental parameters. These ...

We develop a mixed-frequency, tree-based, gradient-boosting model designed to assess the default risk of privately held firms in real time. The model uses data from publicly-traded companies to ...

When discussing learning transfer—the ability to apply previous knowledge, skills, and strategies to new contexts or situations—we should also be mindful of our learners’ cognitive load. Cognitive ...

A strategy borrowed from generative AI — train cheaply on the familiar, then fine-tune on the hard problem — can cut the number of expensive physics simulations needed by nearly a factor of ten. But a ...