Although existing research has confirmed the importance of higher-order structures in identifying key nodes within networks, the challenge remains on how to effectively integrate different types of ...

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 ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking ...