Skip to content

Pure Tensorflow implementation of the SGR layer as proposed in "Symbolic Graph Reasoning Meets Convolutions" .

Notifications You must be signed in to change notification settings

julianschoep/SGRLayer

Repository files navigation

SGRLayer

Pure Tensorflow implementation of the SGR layer as proposed in "Symbolic Graph Reasoning Meets Convolutions". This work makes several assumptions as to how the authors thought about certain implementation details. Therefore, in no way is this implementation guaranteed to produce correct or similar results as in the paper.

We additionally add the fasttext embeddings and adjacency matrix used in our experiments, The image below shows the adjacency matrix we used. adj_mat

Liang, Xiaodan, et al. "Symbolic graph reasoning meets convolutions." Advances in Neural Information Processing Systems. 2018.

About

Pure Tensorflow implementation of the SGR layer as proposed in "Symbolic Graph Reasoning Meets Convolutions" .

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages