mlsanityData to 14 Oct 2026

DynamicGEM: A Library for Dynamic Graph Embedding Methods

arXiv 1811.10734 ↗First posted 26 Nov 2018cs.LG cs.AI cs.SIcited by 8

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Abstract (arXiv)

DynamicGEM is an open-source Python library for learning node representations of dynamic graphs. It consists of state-of-the-art algorithms for defining embeddings of nodes whose connections evolve over time. The library also contains the evaluation framework for four downstream tasks on the network: graph reconstruction, static and temporal link prediction, node classification, and temporal visualization. We have implemented various metrics to evaluate the state-of-the-art methods, and examples of evolving networks from various domains. We have easy-to-use functions to call and evaluate the methods and have extensive usage documentation. Furthermore, DynamicGEM provides a template to add new algorithms with ease to facilitate further research on the topic.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Nov 2018.

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Citing papers per year: 2021: 2; 2022: 0; 2023: 3; 2024: 3.

8 papers.