Teaching

Student Publications

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)

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)

WiSe 2023/24 (click to expand)

SoSe 2023 (click to expand)

WiSe 2022/23 (click to expand)

SoSe 2022 (click to expand)

WiSe 2021/22 (click to expand)

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)

SoSe 2021 (click to expand)

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)

WiSe 2020/21 (click to expand)

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