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ECSE-6810: Introduction to Probabilistic Graphical Models
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Introduction to Probabilistic Graphical Models
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ECSE-6810
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This course covers topics related to learning and inference with different types of Probabilistic Graphical Models (PGMs). It also demonstrates the application of PGMs to different fields. The course covers both directed and undirected graphical models, both parameter and structure learning, and both exact and approximated inference methods.
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3 credits
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Prereqs:
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none
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Detailed View
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< th class = "spring season-label" > Spring< / th >
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< th class = "fall season-label" > Fall< / th >
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< th colspan = "2" > < / th >
< th class = "summer2 midsum-label" > (Session 1)< / th >
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< th class = "year" > 2023< / th >
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Introduction To Probabilistic Graphical Models (3c)
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< li > Qiang Ji< / li >
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Seats Taken: 0/30
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< th class = "year" > 2022< / th >
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Introduction To Probabilistic Graphical Models (3c)
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< li > Qiang Ji< / li >
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Seats Taken: 5/30
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< th class = "year" > 2021< / th >
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Introduction To Probabilistic Graphical Models (3c)
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< li > Qiang Ji< / li >
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Seats Taken: 17/30
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Introduction To Probabilistic Graphical Models (3c)
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< li > Qiang Ji< / li >
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Seats Taken: 27/30
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Introduction To Probabilistic Graphical Models (3c)
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< li > Qiang Ji< / li >
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Seats Taken: 19/36
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< th class = "year" > 2015< / th >
< td class = "term spring not-offered" >
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< td class = "term fall not-offered" >
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Introduction To Probabilistic Graphical Models (3c)
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< ul class = "prof-list" >
< li > Qiang Ji< / li >
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Seats Taken: 8/30
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< td class = "term spring not-offered" >
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< td class = "term fall not-offered" >
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< td class = "term fall not-offered" >
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< td class = "term fall not-offered" >
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< td class = "term fall not-offered" >
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