Learning structural manipulability in gate-level netlists with graph neural networks
Read the original at arxiv.org→arXiv:2607.16245v1 Announce Type: new Abstract: Gate-level netlists exhibit intrinsic structural properties that influence signal propagation independently of functional simulation. We define a topology-driven...
Original headline: "Learning Structural Manipulability in Gate-Level Netlists Using Graph Neural Networks"