divelab/DIG
DIG is a Python library providing implementations of graph neural network research methods for graph representation learning, generation, and explainability.
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DIG (Dive Into Graphs) is a research library for graph deep learning that provides modular implementations of graph neural networks, graph generation models, self-supervised learning methods, and explainability techniques for graph-structured data. It includes benchmarks, tutorials, and example implementations to support research and development in graph representation learning.
Frequently asked
- What is divelab/DIG?
- DIG is a Python library providing implementations of graph neural network research methods for graph representation learning, generation, and explainability.
- Is DIG open source?
- Yes — divelab/DIG is open source, released under the GPL-3.0 license.
- What language is DIG written in?
- divelab/DIG is primarily written in Python.
- How popular is DIG?
- divelab/DIG has 2k stars on GitHub.
- Where can I find DIG?
- divelab/DIG is on GitHub at https://github.com/divelab/DIG.