MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy

Haitian Jiang, Renjie Liu, Zengfeng Huang +5

Among the many variants of graph neural network (GNN) architectures capable of modeling data with cross-instance relations, an important subclass involves layers designed such that…