Ruqiong Zhang

Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module

Graph Neural Networks (GNNs), a type of neural network that can learn from graph-structured data through neighborhood information aggregation, have shown superior performance in various downstream tasks. However, as the number of layers increases, node representations becomes indistinguishable, whic…