Teaching

Winter term 2022/2023

Machine Learning II

  • Nihat Ay & Manfred Eppe
  • lecture & exercise for Data Science (DSBS)
  • lecture: Tuesdays, 15:00 – 16:30, Room K – 0506
  • exercise:
    – Group 1: Thursdays, 9:45 – 11:15, Room O – 0.007
    – Group 2: Thursdays, 11:30 – 13:00, Room A – 1.16
  • more Info: Stud.IP

Das Kino-Seminar: Können Maschinen intelligent sein?

  • Nihat Ay & Manfred Eppe
  • Wednesdays, 11:30 – 13:00
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • more Info: PDF, Stud.IP
  • Timetable: PDF

Research Seminar Data Science Foundations

  • Wednesdays, 15:00 – 16:30
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002

Summer term 2022

Machine Learning I

  • Nihat Ay, Manfred Eppe & Csongor Várady
  • lecture & exercise for Data Science (DSBS)
  • lecture: Wednesdays, 9:45 – 11:15, Room K – 0506
  • exercise:
    – Group 1: Thursdays, 9:45 – 11:15, Room A – 0.01
    – Group 2: Thursdays, 11:30 – 13:00, Room D – 0.011
    – Group 3: Tuesday, 11:30 – 13:00, Room A – 0.14
  • electronic exam: September 14th, 2022
  • more Info: Stud.IP

Winter term 2021/2022

Generieren von Strukturen in Bildern – Die Gibbs-Sampling-Methode (student team project)

  • Nihat Ay & Csongor Várady
  • Student team project for Informatik-Ingenieurwesen (IIW)
  • more info: PDF
  • Timetable: PDF

Das Kino-Seminar: Können Maschinen intelligent sein?

  • Nihat Ay
  • Thursdays, 11:30 – 13:00
  • Location: Blohmstraße 15 (HIP One), 5. Stock, Raum 5.002
  • more info: PDF, Stud.IP
  • Timetable: PDF

Presentations to “Ex Machina” – November 18, 2021:
01-Turing-Test.pdf
02-Chinesisches-Zimmer-Philosophischer-Zombie-und-Marys-Zimmer.pdf
03-Weak-vs-Strong-AI.pdf

Presentations to “I, Robot” – December 16, 2021:
05-ThreeLawsAsimov.pdf
06-Trolley-Problem.pdf
07-Autonomous_Driving.pdf

Presentations to “AlphaGo – January 27, 2022”:
08-Historischer-Kontext-Alphago.pdf
09-DeepBlueAlphaGo.pdf
10-Singularitat.pdf


Summer term 2021

Gradientenmethoden in der Lerntheorie (Seminar)

  • Nihat Ay
  • Masterstudierende ECTS-Punkte: 3

The following courses and seminars took place at the Max Planck Institute for Mathematics in the Sciences and the Leipzig University.


Winter term 2020/2021

Kernel Methods in Learning Theory


Recent Developments Towards a New Theory of Generalisation (Seminar)


Summer term 2019

Artificial Neural Networks and Machine Learning: Theoretical Foundations II

  • Nihat Ay
  • Thursdays, 11:15 – 12:45
  • Location: MPI MiS, A3 02
  • more info

Winter term 2018/2019

Artificial Neural Networks and Machine Learning: Theoretical Foundations I


Summer term 2017

Information Theory II

  • Nihat Ay
  • Tuesdays, 11:00 – 12:30
  • Location: MPI MiS, A3 02

Winter term 2016/2017

Information Theory I

  • Nihat Ay
  • Tuesdays, 11:00 – 12:30
  • Location: MPI MiS, A3 02

Summer term 2016

Grundlagen der Robotik und Seminar Morphological Computation

  • Keyan Ghazi-Zahedi
  • Tuesdays, 13:00 – 15:00
  • Location: University Leipzig, SG 2-14

Summer term 2015

Reinforcement Learning – An Introduction

  • Keyan Ghazi-Zahedi
  • Thursdays, 10:15 – 11:45
  • Location: A2, MPI MiS

Winter term 2014/2015

Geometric Aspects of Graphical Models and Neural Networks

  • Nihat Ay, Guido Montufar
  • Wednesdays, 10:15 – 11:45; first on November 26th
  • Location: A2, MPI MiS

Summer term 2013

Information Theory II

  • Nihat Ay
  • Wednesdays, 11:30 – 13:00; first on April 17th
  • Location: A2, MPI MiS

Winter term 2012/2013

Information Theory

  • Nihat Ay
  • Wednesdays, 11:00 – 12:30; first on October 10th
  • Location: A2, MPI MiS

Winter term 2011/2012

Second part of the IMPRS Ringvorlesung “Higher Dimensions”

  • Nihat Ay
  • Date: 9.,23.,30. November and 7., 14. December

Winter term 2010/2011

Stochastische Prozesse

  • Nihat Ay
  • Thursdays, 15:15 – 16:45, Hs 15

Optimierung und Komplexität

  • Nihat Ay

Summer term 2010

Stochastic Differential Equations

  • Nihat Ay
  • It will take place on Wednesdays, starting April 14, at 10:15 in A1.

Summer term 2009

Mathematical Learning Theory and Neural Networks

  • Nihat Ay

Summer term 2007

Concepts of Causality in Biology and Medicine (Seminar)

  • Korbinian Strimmer & Nihat Ay

Quantum Mechanics: basic mathematical structures and their operational interpretation

  • Arleta Szkola

Winter term 2006/2007

Information Theory II

  • Arleta Szkola

Random Graphs – New Developments Beyond the Erdös-Renyi Model

  • Tyll Krüger

Summer term 2006

Information Theory I

  • Arleta Szkola

Graphical Models and Causality

  • Nihat Ay

Scroll to Top