SpaceLearner/Awesome-DynamicGraphLearning
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
This collection helps researchers and practitioners explore cutting-edge methods for analyzing dynamic (temporal) graphs, which are networks that change over time. It compiles academic papers and associated code that apply machine learning, especially deep learning, to understand how relationships and entities evolve. Anyone working with systems where connections shift, such as social networks, financial markets, or biological interactions, would find this useful for staying current with research.
705 stars. No commits in the last 6 months.
Use this if you are a researcher or advanced practitioner interested in the latest advancements and foundational knowledge in machine learning techniques for evolving network structures.
Not ideal if you are looking for an off-the-shelf software tool or a basic introduction to graph theory, as this resource focuses on advanced research papers and code implementations.
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Jun 04, 2025
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