2 papers
cs.DS2026
Near-Optimal Four-Cycle Counting in Graph Streams
Sebastian Lüderssen, Stefan Neumann, Pan Peng
We study four-cycle counting in arbitrary order graph streams. We present a 3-pass algorithm for -approximating the number of four-cycles using $\widetilde{O}(m/\s…
cs.LG2026
Message Passing on the Edge: Towards Scalable and Expressive GNNs
Pablo Barceló, Fabian Jogl, Alexander Kozachinskiy +3
Graph neural networks (GNNs) are widely used in graph learning and most architectures propagate information by passing messages between vertices. In this work, we shift our attenti…