Data Science Advanced Seminar "Incomplete Network Imbedding"
-
Updated
Sep 1, 2020 - Python
Data Science Advanced Seminar "Incomplete Network Imbedding"
Zero-to-hero for Graph Neural Networks
Implementations of different NLP tasks
Tensorflow implementation of HARP (https://research.google.com/pubs/pub46519.html)
My implementation of Deepwalk in PyTorch
A newly interpreted code of C++ project `SMORe`, which developed in Python to enhance the usage-flexibility and migration-potential.
This notebook is part of a project on Graph Embedding Techniques. It's a comparison between DeepWalk and Node2Vec using SkipGram applied to a dataset called Github Social Network. I did several tests with different p and q values for Node2Vec, the last p = 0.25 and q = 0.25 were the ones that gave me the best result.
Implementing deep learning models from an under the hood perspective.
Torch geometric compatible node embedders
Inverstigate different graph embedding algorithms
PyTorch implementation of Splitter graph node embeddings
GitHub repository vulnerability detection and metrics.
Graph Embeddings for Recommender Systems
Add a description, image, and links to the deepwalk topic page so that developers can more easily learn about it.
To associate your repository with the deepwalk topic, visit your repo's landing page and select "manage topics."