2023W

• Introduction to Machine Learning / 194.025 / VU
• Machine Learning Algorithms and Applications / 194.101 / PR
• Project in Computer Science 1 / 194.145 / PR
• Seminar in Artificial Intelligence - Theoretical Aspects of Machine Learning / 194.118 / SE
• Theoretical Foundations and Research Topics in Machine Learning / 194.100 / VU

• Weisfeiler and Leman Return with Graph Transformations / Jogl, F., Thiessen, M., & Gärtner, T. (2022). Weisfeiler and Leman Return with Graph Transformations. In 18th International Workshop on Mining and Learning with Graphs - Accepted Papers. 18th International Workshop on Mining and Learning with Graphs, Grenoble, France. https://doi.org/10.34726/3829
  Download: Full paper as PDF (439 KB)
• Reducing Learning on Cell Complexes to Graphs / Jogl, F., Thiessen, M., & Gärtner, T. (2022). Reducing Learning on Cell Complexes to Graphs. In ICLR 2022 Workshop on Geometrical and Topological Representation Learning. ICLR 2022 Workshop on Geometrical and Topological Representation Learning, International. https://doi.org/10.34726/3421
  Download: Paper as PDF (263 KB)
• Historian: A Large-Scale Historical Film Dataset with Cinematographic Annotation / Helm, D., Jogl, F., & Kampel, M. (2022). Historian: A Large-Scale Historical Film Dataset with Cinematographic Annotation. In 2022 IEEE International Conference on Image Processing (ICIP) (pp. 2087–2091). https://doi.org/10.1109/ICIP46576.2022.9897300
  Project: VHH (2019–2023)
• Do we need to Improve message passing? Improving graph neural networks with graph transformations / Jogl, F. (2022). Do we need to Improve message passing? Improving graph neural networks with graph transformations [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.103141
  Download: PDF (897 KB)