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 ...
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 ...