Graph technology is allowing pharma to model data in a way that offers invaluable insights for marketing, R&D and compliance teams alike.

Edges and nodes form the core elements of heterogeneous graphs (HGs). However, existing heterogeneous graph neural networks (HGNNS) largely rely on meta-paths to capture semantic information of nodes, ...

About PyTorch implementation of MolGAN: MolGAN: An implicit generative model for small molecular graphs.

Benefiting from exploiting the data topological structure, graph convolutional network (GCN) has made considerable improvements in processing clustering tasks. The performance of GCN significantly ...

Visualization of a PyTorch 2D tensor on Cuda device using OpenGL, without the need to transfer data to the CPU. The visualization is real-time, meaning that any changes to the tensor within the render ...