Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined
| Date | Stars |
|---|---|
| 2026-07-24 | 282 |
| 2026-07-25 | 282 |
| 2026-07-28 | 282 |
| 2026-07-30 | 282 |
| 2026-07-31 | 282 |
| 2026-08-06 | 282 |
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# Graph Neural Networks and Recommendations
A list of interesting graph neural networks (GNN) material with a primary interest in recommendations and [tensorflow](https://github.com/tensorflow/tensorflow) that is continually updated and refined
- [TensorFlow Implementations](#tensorflow-implementations)
- [Articles](#articles)
- [Videos](#videos)
- [Public Datasets](#public-datasets)
- [Recommendation Algorithms](#recommendation-algorithms)
- [Research Papers](#research-papers)
- [Relational Representation Learning](#relational-representation-learning)
- [Survey papers](#survey-papers)
- [Models](#models)
- [Applications](#applications)
## TensorFlow Implementations
- **[Graph Nets in TensorFlow by DeepMind](https://github.com/deepmind/graph_nets)**
- **[Colab Notebook For Graph Nets and Item Connections / Recommendations](https://colab.research.google.com/github/deepmind/graph_nets/blob/master/graph_nets/demos/sort.ipynb)**
- **[Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering](https://github.com/mdeff/cnn_graph)**
- **[Semi-Supervised Classification with Graph Convolutional Networks](https://github.com/tkipf/gcn)**
- **[GraphSAGE](https://github.com/williamleif/GraphSAGE)**
- **[Large-Scale Learnable Graph Convolutional Networks](https://github.com/divelab/lgcn/)**
- **[RippleNet](https://github.com/hwwang55/RippleNet)**
- **[MKR (multi-task learning for knowledge graph enhanced recommendation)](https://github.com/hwwang55/MKR)**
- **[DeepRec](https://github.com/cheungdaven/DeepRec)**
- **[OpenRec](https://github.com/ylongqi/openrec)**
- **[Graph Attention Networks](https://github.com/PetarV-/GAT)**
- **[Variational Graph Auto-Encoder](https://github.com/limaosen0/Variational-Graph-Auto-Encoders)**
- **[Adversarially Regularized Graph Autoencoder](https://github.com/Ruiqi-Hu/ARGA)**
- **[Deep Recursive Network Embedding with Regular Equivalence](https://github.com/tadpole/DRNE)**
- **[DeepWalk](https://github.com/triandicAnt/GraphEmbeddingRecommendationSystem)**
- **[GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model](https://github.com/snap-stanford/GraphRNN)**
- **[Diffusion Convolutional Recurrent Neural Network](https://github.com/liyaguang/DCRNN)**
- **[Spatio-Temporal Graph Convolutional Networks](https://github.com/VeritasYin/STGCN_IJCAI-18)**
## Articles
- **[A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)](https://towardsdatascience.com/a-gentle-introduction-to-graph-neural-network-basics-deepwalk-and-graphsage-db5d540d50b3)**
- **[PinSage: A new graph convolutional neural network for web-scale recommender systems](https://medium.com/pinterest-engineering/pinsage-a-new-graph-convolutional-neural-network-for-web-scale-recommender-systems-88795a107f48)**
- **[Model-Based Machine Learning and Making Recommendations](http://mbmlbook.com/Recommender.html)**
- **[Machine Learning for Recommender systems from Recombee](https://medium.com/recombee-blog/machine-learning-for-recommender-systems-part-1-algorithms-evaluation-and-cold-start-6f696683d0ed)**
- **[How Does Spotify Know You So Well?](https://medium.com/s/story/spotifys-discover-weekly-how-machine-learning-finds-your-new-music-19a41ab76efe)**
## Videos
- **[Intro to Graph Convolutional Networks](https://www.youtube.com/watch?v=UAwrDY_Bcdc)**
- **[Graph Convolutional Networks for Node Classification](https://www.youtube.com/watch?v=LFSR27BaNIQ)**
- **[Jure Leskovec - Large-scale Graph Representation Learning](https://www.youtube.com/watch?v=oQL4E1gK3VU)**
- **[Attention in Neural Networks](https://www.youtube.com/watch?v=W2rWgXJBZhU)**
- **[Michael Bronstein - Geometric deep learning on graphs: going beyond Euclidean data](https://www.youtube.com/watch?v=b187J4ndZWY)**
- **[Yann LeCun - Graph Embedding,Excerpt of 42,557 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:96621a16661b323b, topic:awesome, desc:a list of, readme:a list of
matched fp:96621a16661b323b, topic:tensorflow