Learning-augmented maximum flow

Adam Polak, Maksym Zub

Abstract: Highlights•We speed up maximum flow computation in graphs by using predictions.•Prediction is a flow satisfying flow conservation but not necessarily capacities.•We show that such predictions are efficiently learnable.•We compute flow in O(mη) time in m-edge graphs for predictions with L1 error up to η.