Deep Graph Library (DGL) v0.1 beta has just been released !!
The library aims to ease deep learning on graphs. Some core features of DGL:
- Versatile controls over message passing, ranging from low-level operations such as sending along selected edges and receiving on specific nodes, to high-level control such as graph-wide feature updates.
- Transparent speed optimization with automatic batching of computations and sparse matrix multiplication.
- Seamless integration with existing deep learning frameworks.
- Easy and friendly interfaces for node/edge feature access and graph structure manipulation.
- Good scalability to graphs with tens of millions of vertices.
Feel free to ask anything in this forum. Some helpful resources: