15 citations · 42 across the 10 of their papers we have counts for
3 papers · 1 filter
Partitioning Hypergraphs is Hard: Models, Inapproximability, and Applications
Pál András Papp, Georg Anegg, A. N. Yzelman
We study the balanced -way hypergraph partitioning problem, with a special focus on its practical applications to manycore scheduling. Given a hypergraph on nodes, our goal…
Agent-based Graph Neural Networks
Karolis Martinkus, Pál András Papp, Benedikt Schesch +1
We present a novel graph neural network we call AgentNet, which is designed specifically for graph-level tasks. AgentNet is inspired by sublinear algorithms, featuring a computatio…
A Theoretical Comparison of Graph Neural Network Extensions
Pál András Papp, Roger Wattenhofer
We study and compare different Graph Neural Network extensions that increase the expressive power of GNNs beyond the Weisfeiler-Leman test. We focus on (i) GNNs based on higher ord…