Implementation and experiments of graph embedding algorithms.

Reimplementation of Graph Embedding methods by Pytorch.

Make GNN easy to start with

graph embedding spark implementation, include deepWalk, Node2Vec etc

Persona2vec: A Flexible Multi-role Representations Learning Framework for Graphs

推荐算法专题总结相关代码！

面向大连理工大学学者，基于大连理工大学机构知识库，推荐潜在主题词，优化科研方向，促进跨学部、学科、领域科研合作。

Explained Graph Embedding generation and link prediction

Graph Neural Network Embedding

Python Graph Embedding Library for Knowledge graph

Ulya Bayram, Runia Roy, Aqil Assalil, Lamia Ben Hiba, "The Unknown Knowns: A Graph-Based Approach for Temporal COVID-19 Literature Mining", Online Information Review (OIR), COVID-19 Special Issue, 2021.

Graph Search based on Embedding Similarity

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It is a simple machine learning algorithm to get the latent vector of the Molecules from the datasets. After that we address the imbalance problem in the dataset and handle it by using various resampling techniques. Then we measure the performance of the algorithm by deploying various Classifiers.

Developed a specialized RandomWalk algorithm for bipartite graphs on an ingredient dataset to replace allergenic ingredients while maintaining the nutritional value of the dish, and clustered them into 10 main clusters with 6 of them being highly specific.

Codebase for Mathematics BSc thesis on node embeddings with GraphSage and node2vec.