---
id: "/non-llm-neural-networks-ml-foundations/graph-nns/"
title: "graph NNs: 8 curated resources"
url: "https://skillissue.dev/non-llm-neural-networks-ml-foundations/graph-nns/"
---

# graph NNs: 8 curated resources

graph NNs

[Beginner](/non-llm-neural-networks-ml-foundations/beginner/index.md) [Intermediate](/non-llm-neural-networks-ml-foundations/intermediate/index.md) [Advanced](/non-llm-neural-networks-ml-foundations/advanced/index.md) [Expert](/non-llm-neural-networks-ml-foundations/expert/index.md)

8 resources · page 1 of 1

- 

### [DGL](/foundations/llm-fundamentals/dgl/index.md)

by [DGL team](https://www.dgl.ai/)

Deep Graph Library (DGL): framework for deep learning on graphs, with docs and examples.

entity org West en 

- 

### [Geometric Deep Learning (Bronstein et al.)](/foundations/llm-fundamentals/geometric-deep-learning-bronstein-et-al/index.md)

by [Michael Bronstein, Joan Bruna, Taco Cohen and Petar Veličković](https://geometricdeeplearning.com/)

Geometric Deep Learning site (Bronstein et al.): proto-book and lectures on grids, groups, graphs and geodesics.

entity org West en 

- 

### [Graph Network-based Simulators](/foundations/llm-fundamentals/graph-network-based-simulators/index.md)

by [Google DeepMind](https://www.deepmind.com/)

DeepMind learning_to_simulate code on GitHub: graph network-based simulators for particle physics.

entity repo Global — DeepMind London/Stanf en 

- 

### [PyTorch Geometric](/foundations/llm-fundamentals/pytorch-geometric/index.md)

by [PyG team (Matthias Fey)](https://pyg.org/)

PyTorch Geometric (PyG) documentation: library for building and training graph neural networks.

entity org West en 

- 

### [GAT](/foundations/llm-fundamentals/gat/index.md)

by [Petar Veličković et al. (University of Cambridge)](https://www.cam.ac.uk)

arXiv paper (2017) "Graph Attention Networks", introducing GAT, which weights neighbour nodes with masked self-attention.

Advanced–Expert learning_resource paper West en 

- 

### [GCN](/foundations/llm-fundamentals/gcn/index.md)

by [Thomas N. Kipf and Max Welling (University of Amsterdam)](https://www.uva.nl)

arXiv paper (2016) "Semi-Supervised Classification with Graph Convolutional Networks", introducing GCN layers for node classification.

Advanced–Expert learning_resource paper West en 

- 

### [GraphSAGE](/foundations/llm-fundamentals/graphsage/index.md)

by [William L. Hamilton et al. (Stanford University)](https://www.stanford.edu)

arXiv paper (2017) "Inductive Representation Learning on Large Graphs", introducing GraphSAGE for inductive node embeddings.

Advanced–Expert learning_resource paper West en 

- 

### [Relational inductive biases, deep learning, and graph networks](/foundations/llm-fundamentals/relational-inductive-biases-graph-networks/index.md)

by [Peter W. Battaglia et al. (DeepMind)](https://deepmind.google/)

arXiv paper (2018) "Relational inductive biases, deep learning, and graph networks", defining the graph network block that unifies many GNN variants.

Advanced–Expert learning_resource paper West en 

[Plain-text Markdown copy](/non-llm-neural-networks-ml-foundations/graph-nns/index.md)