
Trends in Graph Machine Learning with Michael Bronstein - #446
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Advancements in Graph Machine Learning
This chapter delves into the evolution of computational models for graph machine learning, emphasizing interoperability and the influence of the OpenGraph benchmark. It highlights real-world applications and innovative developments, particularly in drug repositioning and 3D avatar creation, showcasing the impact of graph neural networks across various fields. With insights into future trends and collaborations, the chapter forecasts an optimistic outlook for bridging research with practical applications.
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