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woojeongjin committed Mar 27, 2019
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Expand Up @@ -28,15 +28,15 @@ This page is to summarize important materials about *dynamic (temporal) knowledg
- [Code (TF based)](https://github.com/malllabiisc/HyTE)

## Dynamic Graph Embedding
- [Representation Learning over Dynamic Graphs](https://arxiv.org/abs/1803.04051)
- Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha. ArXiv.
- [DyREP: Learning Representations over Dynamic Graphs](https://openreview.net/forum?id=HyePrhR5KX)
- Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha. ICLR 2019.
- [DyREP: Learning Representations over Dynamic Graphs](https://openreview.net/forum?id=HyePrhR5KX)
- [DynGEM: Deep Embedding Method for Dynamic Graphs](https://arxiv.org/abs/1805.11273)
- Palash Goyal, Nitin Kamra, Xinran He, Yan Liu. ArXiv.
- [Graph2Seq: Scalable Learning Dynamics for Graphs](https://openreview.net/forum?id=Ske7ToC5Km)
- Anonymous, under review at ICLR 2019.
- Shaileshh Bojja Venkatakrishnan, Mohammad Alizadeh, Pramod Viswanath
- [Dynamic Graph Representation Learning via Self-Attention Networks](https://openreview.net/forum?id=HylsgnCcFQ)
- Anonymous, under review at ICLR 2019.
- Aravind Sankar, Yanhong Wu, Liang Gou, Wei Zhang, Hao Yang
- [Continuous-Time Dynamic Network Embeddings](http://ryanrossi.com/pubs/nguyen-et-al-WWW18-BigNet.pdf)
- Giang Hoang Nguyen, John Boaz Lee, Ryan A. Rossi, Nesreen K. Ahmed, Eunyee Koh, Sungchul Kim. WWW 2018.
- [GC-LSTM: Graph Convolution Embedded LSTM for Dynamic Link Prediction](https://arxiv.org/pdf/1812.04206.pdf)
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