Colab Notebooks covering deep learning tools for biomolecular structure prediction and design ...

MGMN consists of a node-graph matching network for effectively learning cross-level interactions between each node of one graph and the other whole graph, and a siamese graph neural network to learn ...

Graph Neural Networks GNNs have become a powerful tool for analyzing graph-structured data, with applications ranging from social networks and recommendation systems to bioinformatics and drug ...

Abstract: Heterogeneous graph neural networks (GNNs) have been successful in handling heterogeneous graphs. In existing heterogeneous GNNs, meta-path plays an essential role. However, recent work ...

Abstract: Graph Neural Networks (GNNs) have been proven to be useful for learning graph-based knowledge. However, one of the drawbacks of GNN techniques is that they may get stuck in the problem of ...

Zhejiang Provincial Key Laboratory of Advanced Chemical Engineering Manufacture Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China ...

College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China ...

By The Learning Network A new collection of graphs, maps and charts organized by topic and type from our “What’s Going On in This Graph?” feature. By The Learning Network Want to learn ...