Mitigating Graph Oversquashing through Global and Local Non-Dissipativity in Differential Equation Graph Neural Networks

SWAN, a novel Differential Equation Graph Neural Network, achieves global and local non-dissipativity through space and weight antisymmetric parameterization, enabling constant information flow rate and mitigating the oversquashing problem in graph neural networks.