6 citations · 9 across the 4 of their papers we have counts for
4 papers
EBCC v0.2: Error bounded compression for weather and climate applications
Langwen Huang, Luigi Fusco, Florian Scheidl +5
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. These data volumes l…
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…
Arrow Matrix Decomposition: A Novel Approach for Communication-Efficient Sparse Matrix Multiplication
Lukas Gianinazzi, Alexandros Nikolaos Ziogas, Langwen Huang +9
We propose a novel approach to iterated sparse matrix dense matrix multiplication, a fundamental computational kernel in scientific computing and graph neural network training. In…
Neural Graph Databases
Maciej Besta, Patrick Iff, Florian Scheidl +5
Graph databases (GDBs) enable processing and analysis of unstructured, complex, rich, and usually vast graph datasets. Despite the large significance of GDBs in both academia and i…