Although naturally occurring proteins form stable defined tertiary structures, it is well known that many proteins with non-natural sequences have unstructured conformations 1,2. This suggests that ...

Abstract: Graph neural networks (GNNs) are emerging machine learning models on graphs. Permutation-equivariance and proximity-awareness are two important properties highly desirable for GNNs. Both ...

If a smaller and simpler library is required see big.js. It's less than half the size but only works with decimal numbers and only has half the methods. It also has fewer configuration options than ...

Abstract: The nature of heterophilous graphs is significantly different from that of homophilous graphs, which causes difficulties in early graph neural network (GNN) models and suggests aggregations ...