Skip to content
This repository was archived by the owner on Jul 22, 2024. It is now read-only.
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 16 additions & 1 deletion README.md
Original file line number Diff line number Diff line change
@@ -1,2 +1,17 @@
# TM-GCN
Pytorch code for TM-GCN method, a Dynamic Graph Convolutional Networks Using the Tensor M-Product
PyTorch code for the TM-GCN method, a dynamic graph convolutional network which uses the tensor M-product. For further information about the method, please see our paper:

```
@inproceedings{malik2021dynamic,
title = {Dynamic Graph Convolutional Networks Using the Tensor {M}-Product},
booktitle = {Proceedings of the 2021 {SIAM} International Conference on Data Mining ({SDM})},
author = {Malik, Osman Asif and Ubaru, Shashanka and Horesh, Lior and Kilmer, Misha E. and Avron, Haim},
year = {2021},
pages = {729--737},
doi = {10.1137/1.9781611976700.82}
}
```

The published version is available at https://doi.org/10.1137/1.9781611976700.82, and a preprint which includes supplementary material is available at https://arxiv.org/abs/1910.07643

If you use our code in any of your work, please reference our paper.
File renamed without changes.
File renamed without changes.
File renamed without changes.