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Graph Neural Networks for Learning System Dynamics

Offered By: MICDE University of Michigan via YouTube

Tags

Data Science Courses Machine Learning Courses Neural Networks Courses Graph Theory Courses Dynamical Systems Courses Computational Modeling Courses

Course Description

Overview

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Explore the application of Graph Neural Networks (GNNs) in learning system dynamics through this insightful 24-minute lecture by Wei Wang from MICDE University of Michigan. Delve into the innovative use of GNNs for modeling complex systems and understanding their dynamic behavior. Gain valuable knowledge on how these advanced neural network architectures can be leveraged to capture intricate relationships and patterns within interconnected systems. Discover the potential of GNNs in enhancing predictive capabilities and improving decision-making processes across various domains. Learn from Wang's expertise as he discusses cutting-edge research and practical implementations of GNNs in the field of system dynamics.

Syllabus

Wei Wang: Graph Neural Networks for Learning System Dynamics


Taught by

MICDE University of Michigan

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