aida-ugent/DeBayes
DeBayes: a Bayesian Method for Debiasing Network Embeddings (ICML 2020).
When analyzing relationships in complex networks, such as social connections or movie preferences, network embedding models can sometimes be unfairly influenced by popular nodes, leading to biased insights. This tool helps researchers and data scientists correct these biases. It takes raw network data and produces debiased network embeddings, offering a more accurate representation of underlying connections.
No commits in the last 6 months.
Use this if your network analysis is producing results that seem skewed by popular entities or highly connected nodes, and you need to ensure your insights are fair and accurate.
Not ideal if you are working with simple datasets where bias from node popularity is not a concern, or if you need a quick, out-of-the-box solution without any parameter tuning.
Stars
8
Forks
2
Language
Python
License
—
Category
Last pushed
Feb 11, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/aida-ugent/DeBayes"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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...