- BSc
**Seminar**(3 ECTS)*Scientific Research and Writing (SE)* - MSc
**Lecture**(3 ECTS)*Theoretical Foundations and Research Topics in Machine Learning (VU)* - MSc
**Project**(3 ECTS)*Machine Learning Algorithms and Applications (PR)* - MSc
**Project**(6 ECTS)*Project in Computer Science 1 (PR)* - MSc
**Seminar**(3 ECTS)*Seminar in Artificial Intelligence - Theoretical Aspects of Machine Learning (SE)* - PhD
**Seminar**(2 ECTS)*für DissertantInnen (SE)*

- Andrei Dragos Brasoveanu, Fabian Jogl, Pascal Welke, Maximilian Thiessen.
**Extending Graph Neural Networks with Global Features.***Learning on Graphs Conference*2023. - Fabian Jogl, Maximilian Thiessen, and Thomas Gärtner.
**Weisfeiler and Leman Return with Graph Transformations.***Mining and Learning with Graphs*ECMLPKDD Workshop 2022. - Fabian Jogl, Maximilian Thiessen, and Thomas Gärtner.
**Reducing Learning on Cell Complexes to Graphs.***Geometrical and Topological Representation Learning*ICLR Workshop 2022. - Dominik Schmidt.
**Dojo: A Large Scale Benchmark for Multi-Task Reinforcement Learning.***Agent Learning in Open-Endedness*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)

Consult this page for more information on how to write a **thesis with our group**.

- Andrei Brasoveanu:
*Extending Graph Neural Networks with Global Features*(MSc Thesis) - Mate Csikos-Nagy:
*Double-Descent in Graph Neural Networks*(BSc Thesis) - Felix Gross:
*Localized Graph Neural Networks*(BSc Thesis) - Bijan Nikkhah:
*Interactive Optimization of Sequence Submodular Functions*(MSc Thesis) - Tin Marin Tunjic:
*Using Temporal Information to Improve Learning of the Molecular Dynamics Simulation Trajectories for Proteins*(MSc thesis)

- Peter Blohm -
*Breaking the Radon Machine - Investigating the Robustness of a Machine Learning Parallelization Scheme*(BSc Thesis) - Dominik Gall:
*How to Predict the Effectiveness of Bacteriophages*(BSc Thesis) - Nikola Georgiev:
*Predictive Maintenance of Damper Systems in the Real World Based on Simulated Data*(BSc thesis) - Sabrina Herbst: *Analysis of Bacteriophages—Predicting Hosts of Bacteriophages Based on
- Maximilian Holzmüller:
*Generating Levels with NEAT and Stochastic Gradient Descent*(BSc thesis) - Fabian Jogl:
*Do we need to Improve Message Passing? Improving Graph Neural Networks with Graph Transformations*(MSc thesis) - Philipp Lenz:
*Measuring Textual Reasoning in Neural Networks with External Memories*(BSc thesis) - Maximilian Plattner:
*On SGD with Momentum*(MSc Thesis) - Dominik Schmidt:
*Generalization and Transfer Learning in Multi-Task Reinforcement Learning*(BSc thesis) - Thomas Schmied:
*Self-supervised offline reinforcement learning for real-world decision-making agents*(MSc thesis) Molecular Sequence Data* (BSc thesis) - Fabian Traxler:
*Antibody-Antigen Binding Affinity Prediction through the use of geometric deep learning*(MSc thesis) - Philip Vonderlind:
*Domain Transfer for Multi-Agent Reinforcement Learning*(BSc thesis)

- BSc
**Lecture**(6 ECTS)*Introduction to Machine Learning (VU)* - BSc
**Seminar**(3 ECTS)*Scientific Research and Writing (SE)* - MSc
**Lecture**(3 ECTS)*Theoretical Foundations and Research Topics in Machine Learning (VU)* - MSc
**Project**(3 ECTS)*Machine Learning Algorithms and Applications (PR)* - MSc
**Project**(6 ECTS)*Project in Computer Science 1 (PR)* - MSc
**Seminar**(3 ECTS)*Seminar in Artificial Intelligence - Theoretical Aspects of Machine Learning (SE)* - PhD
**Seminar**(2 ECTS)*für DissertantInnen (SE)*

- MSc
**Lecture**(3 ECTS)*Theoretical Foundations and Research Topics in Machine Learning (VU)* - MSc
**Seminar**(3 ECTS)*Seminar in Artificial Intelligence - Theoretical Aspects of Machine Learning (SE)* - MSc
**Project**(3 ECTS)*Machine Learning Algorithms and Applications (PR)* - MSc
**Project**(6 ECTS)*Project in Computer Science 1 - Machine Learning Algorithms and Applications (PR)* - BSc
**Seminar**(3 ECTS)*Scientific Research and Writing (SE)*

- MSc
**Lecture**(3 ECTS)*Theoretical Foundations and Research Topics in Machine Learning (VU)* - MSc
**Seminar**(3 ECTS)*Seminar in Artificial Intelligence - Theoretical Aspects of Machine Learning (SE)* - MSc
**Project**(3 ECTS)*Machine Learning Algorithms and Applications (PR)* - MSc
**Project**(6 ECTS)*Project in Computer Science 1 - Machine Learning Algorithms and Applications (PR)* - BSc
**Seminar**(3 ECTS)*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 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