Nature

A meta-learning framework to mitigate negative transfer in transfer learning applicable to drug design

Data sparseness is a major limiting factor for deep machine learning. In the natural sciences, data distributions are heterogeneous. For instance, in chemistry and early-phase drug discovery, compound ...
Nature

Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting

We investigate the potential of graph neural networks (GNNs) for transfer learning and improved molecular property prediction in the context of funnels or screening cascades characteristic of drug ...
EurekAlert!

Transfer learning in motor imagery brain computer interface: a review

Mingai Li, received her B.Sc. degree and M.Sc. degree from Daqing Petroleum Institute, Heilongjiang, China, in 1987 and 1990 respectively, and Ph.D. degree from Beijing University of Technology, ...
techtimes

Transfer Learning Slashes Cosmology AI Costs: Neutrino Mass Degeneracy Triggers Negative Transfer

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 ...