Eitan Levin

On Transferring Transferability: Towards a Theory for Size Generalization

2025

Many modern learning tasks require models that can take inputs of varying sizes. Consequently, dimension-independent architectures have been proposed for domains where the inputs are graphs, sets, and point clouds. Recent work on graph neural …