Probabilistic Generative Models: Lab ExercisesSubmission: Lab exercises must be submitted on the following ecampus page: You must submit only two files: your report as a PDF file and your code as a ipynb file. Please, only submit one time per group, and put all group members name at the beginning of each document. Deadlines (2022):
Deadlines are hard, the submission website automatically close after them, so I strongly advise to not submit during the last minutes in order to avoid problems. Groups: There should be 1, 2 or 3 students per group. You can not change groups between submission (except if you have problems with other students in your group, please send me an email in this case). I expect a stronger work from a group of three students, e.g. an average assessment (i.e. grade of 10/20) for a group of 1-2 will be considered as bad (below 10/20) for a group of 3. Report instructionsLab exercises comprise two parts:
So the question is: what do you need to write in the report? There are no specific instruction! You must think about the report as an essay: the objective of the report is that you convince me that you understand the theoretical foundation of the model and how to implement it in practice. Use your own word and notations, try to process the course and the lab exercise and explain them to me. Do not write handwavy explanation. You should probably use Latex for this. Length: 3-6 pages, but these are not hard limits - you can do less, you can do a little more. Just don’t write too much, go to the essential (this is not a paper, do not try to write a related work section or anything like this — but you can try to build bridges between course concepts or concepts outside the course). Formal notations with minimum writing to be understandable. Just convince me that you know what you are talking about. :) Advice: do not postpone this to the last minute. It is not something that you can do at the last minute. Scoring: as long as you do the work seriously, that you commented the code you wrote and you submit a nice report, I will give you a good grade. Do not worry if you did not succeed to do everything or if you didn’t understand something. If you explain in the report what you did not succeed, and I can see you did some effort, I will give you a good grade. Lab exercise 1: Variational Auto-EncodersIf the link for the link to download the data does not work, try to download it from here. Report guidelines:
Lab exercise 2: Restricted Boltzmann Machine with continuous observationsReport guidelines:
Lab exercise 3: Real NVP normalizing flow
Report guidelines:
|