torch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
- Skills
- Scientific
- 0
What it does and how to use it
A skill that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
- No commands to memorize: you talk in plain language and the skill does the rest.
Install (Claude Code)
mkdir -p .claude/skills/torch-geometric && curl -fsSL https://doutorai.pt/data/lib/skills__torch-geometric.md -o .claude/skills/torch-geometric/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
---
name: torch-geometric
description: "Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning."
---
# PyTorch Geometric (PyG)
## Overview
PyTorch Geometric is a library built on PyTorch for developing and training Graph Neural Networks (GNNs). Apply this skill for deep learning on graphs and irregular structures, including mini-batch processing, multi-GPU training, and geometric deep learning applications.
## When to Use This Skill
This skill should be used when working
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