Is it suitable for molecular modeling?

Yes, PyG is widely used in bioinformatics and chemistry. This skill includes patterns for loading molecular datasets and predicting chemical properties.

Can this skill help with large graph datasets?

Yes, the skill includes implementation patterns for mini-batching, neighbor sampling, and distributed training to handle graphs that exceed memory limits.

Does it support custom GNN architectures?

Absolutely. It provides specific guidance on inheriting from the MessagePassing class to create custom aggregation, message, and update functions.

What is PyTorch Geometric (PyG) used for?

PyG is a library built on PyTorch for developing Graph Neural Networks (GNNs) to analyze data structured as graphs, such as social networks, molecules, and citation maps.

PyTorch Geometric (PyG) for Claude

Name: PyTorch Geometric (PyG) for Claude
Author: Microck

byMicrock

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Data Science & ML

Implements high-performance Graph Neural Networks and geometric deep learning architectures using the PyTorch Geometric library.

PyTorch Geometric (PyG) is a specialized Claude Code skill designed to streamline the development of Graph Neural Networks (GNNs). It provides Claude with the domain-specific knowledge required to handle irregular data structures like social networks, molecular graphs, and 3D point clouds. This skill enables efficient implementation of node and graph classification, link prediction, and heterogeneous graph processing. It includes optimized patterns for mini-batching, multi-GPU training, and custom message-passing layers, making it an essential tool for developers working on complex relational data and geometric deep learning applications.

Key Features

01Templates for custom message-passing and neighborhood aggregation layers

02Heterogeneous graph support for complex multi-type node and edge relationships

0381 GitHub stars

04Support for 40+ convolutional layers including GCN, GAT, and GraphSAGE

05Efficient mini-batch processing for large-scale graph datasets

06Comprehensive integration with benchmark datasets like Cora, QM9, and Planetoid

Use Cases

01Molecular property prediction for drug discovery and chemical research

023D geometric data processing for point clouds and mesh analysis

03Social network analysis for community detection and influence prediction

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/ordinary-claude-skills torch_geometric

For use in Claude.ai and ChatGPT

Download Skill