- MSc
**Lecture***Theoretical Foundations and Research Topics in Machine Learning (VU)* - MSc
**Seminar***Theoretical Aspects of Machine Learning Algorithms (SE)* - MSc
**Project***Machine Learning Algorithms and Applications (PR)* - BSc
**Seminar***Scientific Research and Writing (SE)*

- Thomas Schmied:
*Self-supervised offline reinforcement learning for real-world decision-making agents*(MSc thesis) - Fabian Jogl:
*Using Structural Information to Improve Graph Neural Networks*(MSc thesis) - Dominik Schmidt:
*Generalization and Transfer Learning in Multi-Task Reinforcement Learning*(BSc thesis) - Maximilian Holzmüller:
*Procedural Level Generation for Video Games*(BSc Thesis)

- Dominik Schmidt.
**Dojo: A Large Scale Benchmark for Multi-Task Reinforcement Learning.***Agent Learning in Open-Endedness*ICLR Workshop 2022. - Fabian Jogl, Maximilian Thiessen, and Thomas Gärtner.
**Reducing Learning on Cell Complexes to Graphs.***Geometrical and Topological Representation Learning*ICLR Workshop 2022. - Fares Meghdouri, Thomas Schmied, Tanja Zseby, and Thomas Gärtner.
**Conditional Network Data Balancing With GANs.***Deep Generative Models and Downstream Applications*NeurIPS Workshop 2021. - Dominik Schmidt and Thomas Schmied.
**Fast and Data-Efficient Training of Rainbow: an Experimental Study on Atari.***Deep Reinforcement Learning*NeurIPS Workshop 2021. - Thomas Schmied and Maximilian Thiessen.
**Efficient Reinforcement Learning via Self-supervised learning and Model-based methods.***Challenges of Real-World Reinforcement Learning*NeurIPS Workshop 2020. (pdf)

- Sabrina Herbst:
*Analysis of Bacteriophages—Predicting Hosts of Bacteriophages Based on Molecular Sequence Data*(BSc thesis) - Philip Vonderlind:
*Domain Transfer for Multi-Agent Reinforcement Learning*(BSc thesis)

- MSc
**Lecture***Theoretical Foundations and Research Topics in Machine Learning (VU)* - MSc
**Seminar***Theoretical Aspects of Machine Learning (SE)* - MSc
**Project***Machine Learning Theory (PR)* - MSc
**Project***Machine Learning Algorithms and Applications (PR)* - BSc
**Seminar***Scientific Research and Writing (SE)*

- MSc
**Lecture***Theoretical Foundations and Research Topics in Machine Learning (VU)* - MSc
**Seminar***Theoretical Aspects of Machine Learning (SE)* - MSc
**Project***Machine Learning Theory (PR)* - MSc
**Project***Machine Learning Algorithms and Applications (PR)* - BSc
**Seminar***Scientific Research and Writing (SE)*

- MSc
**Lecture***Theoretical Foundations and Research Topics in Machine Learning*(VU) - MSc
**Seminar***Theoretical Aspects of Machine Learning*(SE) - MSc
**Project***Machine Learning Algorithms and Applications*(PR) - BSc
**Seminar***Scientific Research and Writing*(SE)