palash1992/GEM
A Python package implementing state-of-the-art graph embedding methods including node2vec, SDNE, HOPE, and Laplacian Eigenmaps.
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GEM provides a general framework for graph embedding methods that represent graphs in low-dimensional vector spaces. The library implements multiple embedding techniques—Locally Linear Embedding, Laplacian Eigenmaps, Graph Factorization, HOPE, SDNE, and node2vec—and includes utilities to evaluate embedding quality through graph reconstruction, link prediction, and visualization tasks.
Frequently asked
- What is palash1992/GEM?
- A Python package implementing state-of-the-art graph embedding methods including node2vec, SDNE, HOPE, and Laplacian Eigenmaps.
- Is GEM open source?
- Yes — palash1992/GEM is open source, released under the BSD-3-Clause license.
- What language is GEM written in?
- palash1992/GEM is primarily written in Python.
- How popular is GEM?
- palash1992/GEM has 1.3k stars on GitHub.
- Where can I find GEM?
- palash1992/GEM is on GitHub at https://github.com/palash1992/GEM.