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Course information provided by the Courses of Study 2021-2022.
Probabilistic programming languages are a powerful tool to express randomized computations and model uncertain behavior. This seminar surveys recent research on such languages, from the perspective of programming languages, logic, and verification. The topic naturally divides into three sections. The first part of the course covers the semantics of probabilistic programming languages: what do such programs mean mathematically, especially when the languages are extended with operators for conditioning and inference? The second part of the course covers verification: what does it mean for probabilistic programs to be correct, and how can we formally verify correctness? Finally, the last part of the course covers applications of probabilistic programs.
When Offered Fall.
Permission Note Enrollment limited to: graduate students or permission of instructor.
Prerequisites/Corequisites Prerequisite: CS 4110 or CS 5110 or CS 6110 or permission of instructor.
Comments Students will be able to determine how to apply probabilistic programming to various application domains."Outcomes
- Students will be able to mathematically formalize and rigorously analyze state-of-the-art probabilistic programming languages.
- Students can verify practically important properties of probabilistic programs.
- Students will be able to determine how to apply probabilistic programming to various application domains.
Regular Academic Session.
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- TR Statler Hall 198
- Aug 26 - Dec 7, 2021
Instruction Mode: In Person
Seats are reserved for graduate students. Professional and undergraduate students should add themselves to the waitlist during add/drop. See enrollment page for more details: https://www.cs.cornell.edu/courseinfo/enrollment/cs-6000-level-courses
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