This repository serves as a curated collection of resources, primarily GitHub repositories, related to Graph Convolutional Networks (GCNs) and Graph Attention Networks (GATs). It targets researchers and practitioners in machine learning and deep learning who are working with graph-structured data, offering implementations, tutorials, and applications across various domains.

How It Works

The collection is organized by application area, categorizing GCN and GAT implementations and research papers. This structure allows users to quickly find relevant resources for specific tasks such as text classification, recommendation systems, image segmentation, and traffic flow prediction, among others. The repository acts as a centralized index to the rapidly growing GCN/GAT ecosystem.

Highlighted Details

• Extensive coverage of GCN/GAT implementations across multiple frameworks (TensorFlow, Keras, PyTorch).
• Resources span a wide array of application domains, including NLP, computer vision, recommendation systems, and spatio-temporal data.
• Includes links to key papers, tutorials, and specific implementations for tasks like relation extraction, scene graph generation, and anomaly detection.

Maintenance & Community

This repository is a community-driven collection, with contributions likely coming from various researchers and developers in the graph neural network space. Specific maintainer details or community links are not provided in the README.

Licensing & Compatibility

The licensing for individual repositories linked within this collection varies, as each points to a separate GitHub project. Users must consult the license of each linked repository for its specific terms and compatibility, particularly for commercial use.

Limitations & Caveats

This is a curated list of links and not a unified codebase. Users will need to clone, install, and potentially adapt each individual repository to their specific needs. The README does not provide installation instructions or dependencies for the collection itself, as it is purely an index.