News

Topic Registration (ddl: 18:00 today)

Written on 28.10.25 by Xiao Zhang

Hello everyone,

Ignore this announcement if you have already selected your topic.

For the remaining students, please visit the Google spreadsheet here and enter your name (and student ID) in one of the empty yellow blanks to indicate the topic you would like to present. You can refer to the next… Read more

Hello everyone,

Ignore this announcement if you have already selected your topic.

For the remaining students, please visit the Google spreadsheet here and enter your name (and student ID) in one of the empty yellow blanks to indicate the topic you would like to present. You can refer to the next page for the two research papers associated with each topic. You will be allowed to make the self-selection by 18:00 today (October 28, 2025). 

Cheers,

Xiao

Proseminar Kickoff

Written on 27.10.25 by Xiao Zhang

Dear Students,

This is a reminder that the kickoff will take place at 16:15 today. The location is Room 0.07 in the CISPA C0 building, Stuhlsatzenhaus 5, 66123 Saarbrücken. The room is on the ground floor, right in front of the main entrance.

For your information, I have uploaded the kickoff… Read more

Dear Students,

This is a reminder that the kickoff will take place at 16:15 today. The location is Room 0.07 in the CISPA C0 building, Stuhlsatzenhaus 5, 66123 Saarbrücken. The room is on the ground floor, right in front of the main entrance.

For your information, I have uploaded the kickoff slides. You can find them at: https://cms.cispa.saarland/dgm_ws25/materials/. We will go through the slides during the class.

I look forward to seeing all of you later this afternoon!

Cheers,

Xiao

[Important!] You must register for the examination of this course on LSF by the end of November 16, 2025, in order to receive credits & grades!

Course Description: Deep generative models have been adopted in many AI and ML applications, such as computer vision, natural language processing, and scientific discovery. Recent advances in parametrizing these models using deep neural networks and training them using stochastic optimization methods have enabled scalable modeling of complex, high-dimensional data. In this proseminar, we will look into foundational frameworks and research frontiers of deep generative models. We will cover topics such as variational autoencoders, generative adversarial nets, diffusion models, flow-based models, and autoregressive models.

Each student will be assigned a topic and will present two papers related to the topic throughout the course. The initial presentation will be followed by a Q&A and discussion session, during which you will receive constructive feedback on how to improve your presentation. Your final grade will be largely determined by your performance on the second presentation and the Q&A. At the end of the semester, each student will need to submit a two-page summary of the presented topic.

Course Instructor: Xiao Zhang (xiao.zhang@cispa.de)

Teaching Assistant: Santanu Rathod (santanu.rathod@cispa.de)

Meeting Time: 16:15 - 17:45 weekly on Mondays

Meeting Location: Room 0.07, CISPA C0 Building at Stuhlsatzenhaus 5, 66123 Saarbrücken

Requirements: The required language for the presentations is English. There are no formal requirements for this proseminar, but having taken graduate-level machine learning or optimization courses will be helpful. You are particularly welcome to the course if you are interested in doing research on deep generative models.


Covered Topics

  1. Variational Autoencoders
  2. Generative Adversarial Networks
  3. Normalizing Flows
  4. Autoregressive Models
  5. Continuous Normalizing Flows
  6. Score-based Generative Models
  7. Diffusion Models
  8. Guided Diffusion
  9. Flow Matching
  10. Consistency Models
  11. Masked Diffusion Models
  12. Discrete Flow Matching

(Tentative) Course Schedule

  • Oct 27: Proseminar kickoff – course introduction & overview of the topics
  • Nov 03: Tutorial on how to read & present a research paper
  • Nov 10: Initial presentation – topics 1 & 2 
  • Nov 17: Initial presentation – topics 3 & 4
  • Nov 24: Initial presentation – topics 5 & 6
  • Dec 01: Initial presentation – topics 7 & 8
  • Dec 08: Initial presentation – topics 9 & 10
  • Dec 15: Initial presentation – topics 11 & 12
  • Jan 05: Final presentation
  • Jan 12: Final presentation
  • Jan 19: Final presentation

Grading Rubrics

In-class Participation (15%). Students are expected to attend the weekly meeting and actively participate in the Q&A sessions. Each student is expected to give a total of five inputs (questions or constructive feedback) during the Q&A and discussion sessions throughout the seminar. The instructor and the TA will keep track of the number of questions you have asked and/or comments you have provided throughout the semester, which will count toward your final grade.

Paper Presentation (70%). Each student will be assigned a topic and two papers related to that topic. During the proseminar kickoff, the instructor will give an introduction and all the topics. You will get access to all the prepared research papers during the kickoff. You are allowed to choose one of the topics (first-come, first-served) by the end of October 27. I strongly suggest you make the selection during the seminar kickoff. If you do not choose any topic, you will be randomly assigned a topic the following day.

  • Initial presentation (20%). You will present the first research paper, usually a seminal one regarding the topic, during one of the class meetings in November and December. You have 20 minutes to present the paper, followed by a 25-minute Q&A and discussion session. The instructor, the TA, and other participants will raise questions. You will receive constructive feedback on how to improve your presentation, which should be taken into account in your final presentation.
  • Final presentation (50%). You will present the second research paper, typically a recent one on the topic, during one of the three class meetings in January. Again, you have 20 minutes to present the paper, followed by a 10-minute Q&A session. Most of the questions will be asked by the instructor and the TA.

Written Summary (15%). At the end of the semester, you will need to submit a two-page summary, summarizing the topics you have presented, what you have learned throughout the semester, your reflections, etc.

Bonus: TBD

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