Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking ...
Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback