pedugnat/dynnode2vec
dynnode2vec is a python package that implements algorithms to embed dynamic graphs
This project helps data scientists and researchers understand how complex relationships evolve over time. You input a series of graphs representing a network's state at different moments, and it outputs numerical representations (embeddings) for each node, capturing its role and context within the changing network. This is useful for anyone analyzing dynamic social networks, biological interactions, or evolving infrastructure.
No commits in the last 6 months. Available on PyPI.
Use this if you need to analyze the changing structure of a network and identify patterns or make predictions based on how nodes behave over time.
Not ideal if your network data is static and doesn't change over time, as it's specifically designed for dynamic graphs.
Stars
12
Forks
2
Language
Python
License
MIT
Category
Last pushed
Aug 12, 2022
Commits (30d)
0
Dependencies
4
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/pedugnat/dynnode2vec"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Higher-rated alternatives
eliorc/node2vec
Implementation of the node2vec algorithm.
mims-harvard/decagon
Graph convolutional neural network for multirelational link prediction
mims-harvard/nimfa
Nimfa: Nonnegative matrix factorization in Python
ferencberes/online-node2vec
Node Embeddings in Dynamic Graphs
claws-lab/jodie
A PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in...