Math: Dynamic programming

Budgeted Tree Message-Passing Planner

Before or during graph-neural-network inference, use a tree dynamic program to choose a limited set of active computation nodes and upgraded message-passing edges. A node receives an embedding from an active landmark only when the selected path has enough residual communication radius, so the planner directly optimizes weighted coverage under a joint node-and-edge budget. The resulting active subgraph is then used by a sparse GNN or graph transformer.