Teaching

Teaching

Summer term 2023

Practical course on applying deep learning for image generation.

Alexander Ecker and Timo Lüddecke

Winter term 2022/2023

Seminar where recent deep learning papers are presented and discussed.

Alexander Ecker, Laura Hansel, Richard Vogg, Polina Turishcheva and Timo Lüddecke

Summer term 2022

Seminar where recent computational neuroscience papers are presented and discussed.

Alexander Ecker, Laura Pede, Michaela Vystrčilová, Suhas Shrinivasan

Practical course on applying deep learning for image generation.

Alexander Ecker and Timo Lüddecke

Introduction to Machine Learning

Alexander Ecker

Bachelor’s and Master’s theses

General requirements

We expect prospective students to have substantial knowledge in machine learning, its mathematical foundations and Python programming. We therefore strongly recommend that students interested in doing their thesis in our lab should take our courses on Machine Learning, Deep Learning and took the Fachpraktikum Data Science. Exceptions are possible if well motivated.

Further recommended lectures are:

  • M.Inf.2201: Probabilistic Machine Learning (by Fabian Sinz)
  • B.Inf.1231: Infrastructures for Data Science (by Philipp Wieder)
  • M.WIWI-QMW.0002: Advanced Statistical Inference (by Elisabeth Bergherr)

Please note, our thesis supervision capacity is limited and we receive more thesis inquiries than we are able supervise. Therefore, we have to select candidates. If you are interested, please write an email with the subject “Master’s thesis” or “Bachelor’s thesis” containing one to three sentences about what you would like to work on and your study record to the supervisor stated below.

We will get back to you within a few days. Otherwise, do not hesitate to remind us :).

Thesis offers

Directed Tree Neural Networks
Exploiting the Tree Structure of Neurons: Directed Tree Neural Networks
Supervisor: Martin Ritzert
Embedding Unbranched Segments of Neuronal Dendrites
Embedding Unbranched Segments of Neuronal Dendrites for Neuron Clustering
Supervisor: Martin Ritzert
GraphDINO with Deep Graph Neural Networks
Extend GraphDINO to incorporate modern Graph Neural Networks as their inner model
Supervisor: Martin Ritzert
Protein Structure Analysis
Protein Structure Analysis
Supervisor: Alexander Ecker
Neural Data Science Group
Institute of Computer Science
University of Goettingen