2025
MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks
ICLR 2025poster
We propose a novel approach to compute the MAXCUT in attributed graphs, i.e., graphs with features associated with nodes and edges. Our approach works well on any kind of graph topology and can find solutions that jointly optimize the MAXCUT along with other objectives. Based on the obtained MAXCUT…