nowfound

Life & fun · April 30, 2019

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 →
  • WA
  • Word2vec Algorithm in ~100sloc with NumPy2023 · github.com · ▲72

    Here'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.

  • StarVector2025 · starvector.github.io · ▲311

    Generate SVG code from images and text

  • Model2vec-Rs – Fast Static Text Embeddings in Rust2025 · github.com · ▲60

    Hey 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:…

  • WD
    We 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 · ▲14

    A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018). - benedekrozemberczki/role2vec

More life & fun this month

the category →

Source: Show HN post ↗

Launched alongside, April 2019

the whole month →