Probabilistic Programming (Praktikum)
Sommer semester 2016
Organization
Organizer | Yufei Cai AlumniYufei Cai |
Biweekly meeting | Tuesday 14:15-16:00 in A302 (Übungsraum, Gebäude Informatik/Astronomie) |
Forum | forum-ps.cs.uni-tuebingen.de/c/ppp |
Language | English |
Credits | 6 LP (Im Vorlesungsverzeichnis) |
Description
The world is full of randomness and uncertainty. Modelling random processes help us make better decisions, but it is not always intuitive to work with these models. Probabilistic programming languages enable us to describe complicated probability models and obtain properties relevant for decision making through the power of modern computers. In this module, we learn the probabilistic programming language Figaro and use it to solve practical problems. Knowledge in probability theory is helpful but not required.
Process
We will work through a series of exercises from the textbook, followed by a free project. The code you write are completely public; you are encouraged to share code and help each other.
We meet once every 2 weeks. During a meeting, you will
- report what you did,
- announce what you want to do, and
- discuss your code and goals with other participants and me.
In each of the fortnights between meetings, you will
- read 2-3 chapters of the textbook,
- accomplish your goals announced at the previous meeting, and
- come up with goals for the next meeting.
How much you read and program is completely up to you. The reading assignment in the plan below is merely a guideline. What you accomplish throughout the semester determines your grade. Missing a meeting counts as doing nothing for 2 weeks.
The goals of each fortnight can be either a series of exercises in the textbook or a mini-project related to the readings of the previous fortnight. If several participants choose the same exercise, they must either choose something else or collaborate with each other.
Textbook
Avi Pfeffer. Practical probabilistic programming.
Meetings
12/04 | Organization slides |
Reading: §1, 2, 3 | |
26/04 | First project |
Reading: §4, 5 | |
10/05 | Bayesian and Markov networks |
Reading: §6, 7 | |
24/05 | Collections and objects |
Reading: §8, 9 | |
07/06 | Dynamic systems |
Reading: §10, 11 | |
21/06 | Factors and samplers |
Reading: §12, 13 | |
05/07 | Parameter learning |
19/07 | Final project: proposal |
02/08 | Final project: presentation |
Resources
- Git workshop with slides