chihming / awesome-network-embedding Goto Github PK

Hi, thank you for your list of so many networks.

Is there any directed, weighted and heterogeneous graph with node features? （node features are not text information, just continuous variable）

Look forward to your reply!

The link for BiNE method is outdated. Please replace with the following:
http://staff.ustc.edu.cn/~hexn/papers/sigir18-bipartiteNE.pdf

This year's MLG had a few more papers on networking embedding. Should I add those to the list?

Thanks a lot, for putting together this repo. Would it be possible to add Pytorch-BigGraph?

Pytorch-BigGraph - a distributed system for learning graph embeddings for large graphs.

paper: https://www.sysml.cc/doc/2019/71.pdf
code: https://github.com/facebookresearch/PyTorch-BigGraph

Thank you.

Hi chihming,
I would like to add a nice paper accepted in AAAI 2018 as an oral presentation.
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
paper link: https://arxiv.org/abs/1801.07606
Project link: https://liqimai.github.io/blog/AAAI-18/
code link: https://github.com/liqimai/gcn/tree/AAAI-18/

Hello guys, and thanks for the curated list!
We have been working on this library, it would be great if it could make it into your list!

- **AmpliGraph**
  - Library for learning knowledge graph embeddings with TensorFlow 
  - [[Project]](http://docs.ampligraph.org)
  - [[code]](https://github.com/Accenture/AmpliGraph)

Thanks!

Thanks for putting together this repository! Here's another paper that might be relevant, since it also considers unsupervised network embedding in the context of the task of network alignment.
Mark Heimann, Haoming Shen, Tara Safavi, and Danai Koutra. REGAL: Representation Learning-based Graph Alignment. International Conference on Information and Knowledge Management (CIKM), 2018.

Paper: Arxiv preprint https://arxiv.org/pdf/1802.06257.pdf Official conference link here
Code: https://github.com/GemsLab/REGAL

See: https://arxiv.org/abs/1707.03815

Hi!

Thank you for this awesome repository!

Could you please add the following paper, code, and data link to the repository:
Paper: Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks
Authors: Srijan Kumar, Xikun Zhang, Jure Leskovec
Venue: ACM SIGKDD 2019 (Proceedings of the 25th ACM SIGKDD international conference on Knowledge discovery and data mining)
Project page: http://snap.stanford.edu/jodie/
Code: https://github.com/srijankr/jodie/
All datasets: http://snap.stanford.edu/jodie/

Many thanks,
Srijan

Hi,
I'd suggest to add following items:

1. succinct Pyton3 implementation of node2vec : https://github.com/eliorc/node2vec
2. Attention-based Graph Neural Network for semi-supervised learning https://github.com/dawnranger/pytorch-AGNN
3. Representation Tradeoffs for Hyperbolic Embeddings https://github.com/HazyResearch/hyperbolics
4. An End-to-End Deep Learning Architecture for Graph Classification
   https://github.com/muhanzhang/DGCNN
   https://github.com/muhanzhang/pytorch_DGCNN
5. Discriminative Embeddings of Latent Variable Models for Structured Data
   https://github.com/Hanjun-Dai/pytorch_structure2vec
6. Decagon, Graph Neural Network for Multirelational Link Prediction
   https://github.com/marinkaz/decagon
7. TF implementation for "LINE: Large-scale Information Network Embedding"
   https://github.com/snowkylin/line
8. Keras implementation for "Structural Deep Network Embedding" [SDNE]
   https://github.com/xiaohan2012/sdne-keras
9. Learning to Make Predictions on Graphs with Autoencoders
   https://github.com/vuptran/graph-representation-learning
10. Predicting multicellular function through multi-layer tissue networks
    https://github.com/marinkaz/ohmnet
11. VERSE, Versatile Graph Embeddings from Similarity Measures
    https://github.com/xgfs/verse
12. C++ implementation of node2vec
    https://github.com/xgfs/node2vec-c
13. C++ implementation of DeepWalk
    https://github.com/xgfs/deepwalk-c

Hi,

I wonder if you might find my paper interesting:
https://arxiv.org/abs/1903.03036

Code available at:
https://github.com/DavidMcDonald1993/heat

It deals with embedding attributed networks to a hyperbolic space.

Best wishes,
David McDonald

PyKEEN is a package implementing 30+ knowledge graph embedding models (including some already mentioned in this list). The full list of models is at https://github.com/pykeen/pykeen/#models-30.

Website: https://pykeen.github.io/
Code: https://github.com/pykeen/pykeen
Paper link: http://jmlr.org/papers/v22/20-825.html
PyPI: pip install pykeen
Citation:

@article{ali2021pykeen,
    author = {Ali, Mehdi and Berrendorf, Max and Hoyt, Charles Tapley and Vermue, Laurent and Sharifzadeh, Sahand and Tresp, Volker and Lehmann, Jens},
    journal = {Journal of Machine Learning Research},
    number = {82},
    pages = {1--6},
    title = {{PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings}},
    url = {http://jmlr.org/papers/v22/20-825.html},
    volume = {22},
    year = {2021}
}

This how the page looks. The image is truncated.

Hi, is it possible to add this AAAI'19 paper: ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation
paper: https://arxiv.org/abs/1811.00839
code: https://github.com/zhenv5/atp

https://arxiv.org/abs/1611.08402 (MoNet)
https://arxiv.org/abs/1704.01212 (MPNN)
https://arxiv.org/abs/1710.03059 (EP)