483 citations · 588 across the 24 of their papers we have counts for
4 papers · 1 filter
Demystifying Higher-Order Graph Neural Networks
Maciej Besta, Florian Scheidl, Lukas Gianinazzi +4
Higher-order graph neural networks (HOGNNs) and the related architectures from Topological Deep Learning are an important class of GNN models that harness polyadic relations betwee…
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers
Maciej Besta, Afonso Claudino Catarino, Lukas Gianinazzi +4
Many graph representation learning (GRL) problems are dynamic, with millions of edges added or removed per second. A fundamental workload in this setting is dynamic link prediction…
ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts
Saleh Ashkboos, Langwen Huang, Nikoli Dryden +5
Post-processing ensemble prediction systems can improve the reliability of weather forecasting, especially for extreme event prediction. In recent years, different machine learning…
Learning Combinatorial Node Labeling Algorithms
Lukas Gianinazzi, Maximilian Fries, Nikoli Dryden +3
We present a novel neural architecture to solve graph optimization problems where the solution consists of arbitrary node labels, allowing us to solve hard problems like graph colo…