2 papers
cs.CE2026
Error bounded compression for weather and climate applications
Langwen Huang, Luigi Fusco, Florian Scheidl +4
As the resolution of weather and climate simulations increases, the amount of data produced is growing rapidly from hundreds of terabytes to tens of petabytes. The huge size become…
cs.LG2025
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…