Shypd.aiThe largest open index of AI toolspytorch-GAT is an AI Frameworks & Infra tool that provides a PyTorch implementation of the original Graph Attention Network (GAT) paper. It includes visualization tools for datasets, embeddings, attention mechanisms, and entropy histograms.
Trending
About
pytorch-GAT offers a PyTorch implementation of the Graph Attention Network (GAT) paper by VeliΔkoviΔ et al., designed to facilitate learning and experimentation with GAT and Graph Neural Networks (GNNs). The repository supports both Cora (transductive) and PPI (inductive) examples, making it versatile for different graph-based tasks. A key feature is the `playground.py` file, which enables comprehensive visualizations of the Cora dataset, GAT embeddings, attention mechanisms, and entropy histograms. This allows users to gain deeper insights into how GAT models process and learn from graph data. The tool also provides detailed setup instructions, training scripts for Cora and PPI, and tips for understanding the code, making it accessible for developers and researchers interested in GNNs.
Capabilities
Pricing & Plans
Open Source
Free
FAQs
Trending
