CapsGNN adapts Capsule Neural Networks to Graph Neural Networks for graph classification tasks. It extracts node features in capsule form and leverages routing mechanisms to aggregate information across multiple aspects at the graph level. An attention module incorporated into the architecture handles graphs of varying sizes by focusing on critical substructures, producing multiple embeddings per graph to capture diverse properties.