A Parallel Implementation of Graph2Vec
A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017). - benedekrozemberczki/graph2vec
A Parallel Implementation of Graph2Vec launched on April 30, 2019 with 53 votes, #824 of 3,128 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 7 years on.
In plain words
A Parallel Implementation of Graph2Vec is a software tool that creates vector representations of graphs for machine learning tasks. Developed for researchers and data scientists working with graph-structured data, it uses parallel processing to speed up computations. The tool implements the Graph2Vec algorithm, which converts entire graphs into fixed-size vectors suitable for classification and analysis tasks.
written from the facts on this page · September 2026
Does a similar job
all alternatives →- WAWikipedia2Vec – A tool for learning embeddings of words and entities2018 · wikipedia2vec.github.io · ▲105
Word2vec Algorithm in ~100sloc with NumPy2023 · github.com · ▲72Here's a small demonstration of the fundamental aspects of the word-to-vec algorithm. It's implemented in a single python script and depends only on a single text file for training. It's not meant to be blazingly fast or anything, just a toy example to aid my understanding of how word vectors might be learnt from a corpus.

Model2vec-Rs – Fast Static Text Embeddings in Rust2025 · github.com · ▲60Hey HN! We’ve just open-sourced model2vec-rs, a Rust crate for loading and running Model2Vec static embedding models with zero Python dependency. This allows you to embed text at (very) high throughput; for example, in a Rust-based microservice or CLI tool. This can be used for semantic search, retrieval, RAG, or any other text embedding usecase. Main Features: - Rust-native inference: Load any Model2Vec model from Hugging Face or your local path with StaticModel::from_pretrained(...). - Tiny footprint: The crate itself is only ~1.7 mb, with embedding models between 7 and 30 mb. Performance:…
- WDWe designed and implemented graph projection feature2022 · ▲38
Hi all! I'm one of the developers that were working on this project for some time. In recent months, users started to ask us more frequently about the ability to run algorithms on a part of graph stored in database - subgraph. Now to do this, we extended the implementation of C API we had and brought to you the graph project feature that enables running algorithms on a specific subset of a graph stored in the database. You can now do graph analysis with PageRank, degree centrality, betweenness centrality, or any other algorithm on subgraphs without any additional adjustments. Before you had…
Role2Vec: Learning Role-Based Graph Embeddings2020 · github.com · ▲14A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018). - benedekrozemberczki/role2vec
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