Simple reference implementation of GraphSAGE.
☆1,046May 11, 2020Updated 5 years ago
Alternatives and similar repositories for graphsage-simple
Users that are interested in graphsage-simple are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Representation learning on large graphs using stochastic graph convolutions.☆3,689Aug 4, 2024Updated last year
- A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.☆681Oct 3, 2023Updated 2 years ago
- Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)☆3,121Jul 6, 2023Updated 2 years ago
- Graph Convolutional Networks in PyTorch☆5,398Sep 20, 2020Updated 5 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆143May 8, 2018Updated 7 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Implementation of Graph Convolutional Networks in TensorFlow☆7,378Apr 14, 2023Updated 3 years ago
- Graph Attention Networks (https://arxiv.org/abs/1710.10903)☆3,526Apr 9, 2022Updated 4 years ago
- Python package built to ease deep learning on graph, on top of existing DL frameworks.☆14,271Jul 31, 2025Updated 9 months ago
- The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""☆530Mar 25, 2021Updated 5 years ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆849Dec 13, 2021Updated 4 years ago
- Graph Neural Network Library for PyTorch☆23,716Updated this week
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆666Nov 1, 2022Updated 3 years ago
- ☆508Jan 13, 2021Updated 5 years ago
- DeepWalk - Deep Learning for Graphs☆2,759Jun 14, 2023Updated 2 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- How Powerful are Graph Neural Networks?☆1,282Jul 1, 2021Updated 4 years ago
- Must-read papers on graph neural networks (GNN)☆16,763Dec 20, 2023Updated 2 years ago
- Heterogeneous Graph Neural Network☆1,208May 6, 2020Updated 5 years ago
- links to conference publications in graph-based deep learning☆5,057Feb 7, 2026Updated 2 months ago
- A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).☆806Nov 6, 2022Updated 3 years ago
- An Open-Source Package for Network Embedding (NE)☆1,705Jan 10, 2024Updated 2 years ago
- Must-read papers on network representation learning (NRL) / network embedding (NE)☆2,517Aug 3, 2020Updated 5 years ago
- Implementation of Graph Auto-Encoders in TensorFlow☆1,738Jan 3, 2020Updated 6 years ago
- [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive L…☆508Aug 12, 2022Updated 3 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- ☆2,727Jul 21, 2022Updated 3 years ago
- Semi-supervised learning with graph embeddings☆953Mar 5, 2020Updated 6 years ago
- Repository for benchmarking graph neural networks (JMLR 2023)☆2,653Jun 22, 2023Updated 2 years ago
- A curated list of network embedding techniques.☆2,624Dec 8, 2020Updated 5 years ago
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆495Dec 5, 2018Updated 7 years ago
- Benchmark datasets, data loaders, and evaluators for graph machine learning☆2,085May 6, 2025Updated 11 months ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆476Dec 7, 2022Updated 3 years ago
- Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.☆852Jan 11, 2023Updated 3 years ago
- Generate embeddings from large-scale graph-structured data.☆3,458Mar 3, 2024Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- ☆1,287Nov 5, 2023Updated 2 years ago
- Graph Classification with Graph Convolutional Networks in PyTorch [NeurIPS 2018 Workshop]☆336Oct 16, 2020Updated 5 years ago
- Keras-based implementation of Relational Graph Convolutional Networks☆818Jul 2, 2019Updated 6 years ago
- Graph Convolutional Networks (GCNs)☆918Feb 9, 2018Updated 8 years ago
- Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)☆1,084Feb 15, 2023Updated 3 years ago
- PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.☆1,231Mar 28, 2025Updated last year
- A collection of important graph embedding, classification and representation learning papers with implementations.☆4,803Mar 18, 2023Updated 3 years ago