Factor graph neural networks
The Factor Graph Neural Network (FGNN) extends traditional graph neural networks (GNNs) to capture dependencies among multiple variables, providing a framework capable of representing Max-Product belief propagation for approximate inference in probabilistic graphical models, with demonstrated effectiveness on synthetic and real datasets.
Jan 1, 2020
