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Cognitive Systems

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  11. Cognitive Systems (Seminar)

Masterseminar Kognitive Systeme/Cognitive Systems (SS 2022)

General Information

  • This seminar is open only for master students of the degrees AI, WI, CitH and ISSS.
  • You have to pass our course KogSys-ML-M to be able to participate in the seminar.
  • There will be a limit of 20 students that are able to participate in the seminar.
  • You have to apply for this seminar in a central application procedure. More info in the VC course.
  • You find administrative information at UnivIS.
  • Participants should sign up for the course in the virtual campus.
  • The course is usually offered in the summer term.

Topic: Deep Learning

In recent years, the topic of deep learning gained a lot of interest in the research community. The approaches often outperform traditional machine learning methods. We want to have a look at different approaches, applications and architectures, and the (dis-)advantages of them. We will discuss current research papers in the field.

Recommended Reading / Links / Topics

  • Image/Sound/Text Classification/Segmentation/Regression
  • Concept Disentanglement
  • Autoencoders
  • Capsule Networks
  • Explainable AI
  • Ecological AI
  • Hardware Configurations

    Previous Seminars

    Bachelor/Master-Seminar: Explainable Artificial Intelligence:  [WS 19/20] [WS 20/21]

    KI-Seminare (KI gestern, heute, morgen): [WS 15/16] [WS 16/17] [WS 17/18] [WS 18/19]

    Bachelor Seminare: [WS 04/05] [WS 05/06] [WS 06/07] [WS 07/08] [WS 08/09] [WS 09/10]  [WS 10/11]    [SS 11] [WS 11/12] [WS 12/13] [WS13/14]

    Master Seminare: [SS 05] [SS 06] [SS 08] [SS 09] [WS 09/10] [SS 10]  [WS 11/12] [WS 12/13] [WS 13/14] [SS 20] [SS 21][SS22]

    Reading Clubs:

    • WS 14/15: Cognitive Models for Number Series Induction Problems  [Archiv Page]
    • SS 2014: Experimenting with a Humanoid Robot - Programming NAO to (Inter-)Act  [Archiv Page] 
    • SS 2013: An introduction into statistic data analysis with R  [Archiv Page] 
    • SS 2012: Transfer Learning  [Archiv Page] 
    • SS 2011: Emotion Mining in Images and Text  [Archiv Page] 
    • SS 2010: Aspects of Cognitive Robotics [Archiv Page] 
    • SS 2009: Reading Club Decision Support Systems [Archiv Page] 
    • WS 08/09: Algebraic Foundations of Functional Programming (together with Theoretical Computer Science) [Archiv Page]  
    • SS 2008: Similarity (together with Statistics) [Archiv Page]
    • SS 2007: Automated Theorem Proving with Isabelle (together with Theoretical Computer Science) [Archiv Page]
    • SS 2006: Support Vector Machines [Archiv Page]