Marco Cusumano-Towner, Alexander Lew
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Jan/29 | Tue | 04:00PM-06:00PM | TBD |
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Jan/30 | Wed | 04:00PM-06:00PM | TBD |
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Jan/31 | Thu | 04:00PM-06:00PM | TBD |
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Feb/01 | Fri | 04:00PM-06:00PM | TBD |
Enrollment: Limited: Advance sign-up required
Attendance: Participants must attend all sessions
This course will introduce applied probabilistic programming using the Gen probabilistic programming system. It is designed for researchers familiar with generative probabilistic modeling who are interested in using probabilistic programming tools to accelerate their research. The course will involve a guided tutorial on Gen and possibly workshop time for students to prototype models from their own research areas. Students will be encouraged to experiment with Gen outside of class time.
To sign up for the class please send an email to marcoct@mit.edu briefly describing your research area and any previous experience with mathematical modeling, probabilistic inference, deep learning or probabilistic programming. Also please give a one or two sentence description of a modeling, learning, or inference problem that you would like to solve using probabilistic programming.
Contact: Marco Cusumano-Towner, MARCOCT@MIT.EDU