Gaussian Acyclic Models: Linearity and Identifiability
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Description
This lecture covers Gaussian Acyclic Models (NGAM) focusing on linearity and identifiability. Topics include directed loops, zero mean Gaussian models, support of models, and the importance of model identifiability in learning processes.
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Students will learn the core concepts and techniques of network analysis with emphasis on causal inference. Theory and
application will be balanced, with students working directly with network data th