2018-2019 University Catalog 
    
    May 20, 2024  
2018-2019 University Catalog archived

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CSCI 252 - Neural Networks and Graphical Models


Credits: 3

Prerequisite: CSCI 112. A survey of the major developments in neural and belief networks, from the early perception models of the 1940s through the probabilistic Bayesian networks that are a “hot topic” in artificial intelligence today. Topics include the back-propagation algorithm, simple recurrent networks, Hopfield nets, Kohonen’s Self-Organizing Map, learning in Bayesian networks, and Dynamic Bayesian Networks, with readings from both popular textbooks and the scholarly literature. A major focus of the course is on writing programs to implement and apply these algorithms. Levy.




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