DGL is a graph-centric library that optimizes GNNs via generalized sparse tensor operations, transparent graph-based optimizations, and framework-neutral design, claiming superior speed and memory use over other GNN frameworks.
Neugraph: parallel deep neural network computation on large graphs
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
DGL is a graph-centric library that optimizes GNNs via generalized sparse tensor operations, transparent graph-based optimizations, and framework-neutral design, claiming superior speed and memory use over other GNN frameworks.