Telefon, Fax, E-Mail:

Telefon:	+49 5121 / 883-40390
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Publikationen:

• Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz, Maximilian Stubbemann, Stefan Born, Lars Schmidt-Thieme (2025):
  Physiome-ODE: A Benchmark for Irregularly Sampled Time Sereis Forecasting based on Biological ODEs , in Proceedings of the International Conference on Learning Representations (ICLR).
• Thorben Werner, Johannes Burchert, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
  A Cross-Domain Benchmark for Active Learning, in Neural Information Processing Systems.
• Christian Klötergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
  Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting, in ECML PKDD 2024.
• Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
  Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training, in arXiv:2404.06966. .
• Kiran Madhusudhanan, Gunnar Behrens, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
  ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing, in arXiv:2403.03812.
• Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
  Moco: A Learnable Meta Optimizer for Combinatorial Optimization, in Advances in Knowledge Discovery and Data Mining. PAKDD 2025.
• Tobias Hille, Maximilian Stubbemann, Tom Hanika (2024):
  Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research, in arxiv:2403.08438.
• Maximilian Stubbemann, Tobias Hille, Tom Hanika (2023):
  Selecting Features by their Resilience to the Curse of Dimensionality, in arXiv:2304.02455.
• Maximilian Stubbemann, Gerd Stumme (2023):
  The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks, in Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD.
• Maximilian Stubbemann, Tom Hanika, Friedirch Martin Schneider (2023):
  Intrinsic Dimension for Large-Scale Geometric Learning, in Transactions on Machine Learning Research.
• Maximilian Stubbemann, Gerd Stumme (2022):
  LG4AV: Combining Language Models and Graph Neural Networks for Author Verification, in Advances in Intelligent Data Analysis XX.
• Dominik Duerrschnabel, Maximilian Stubbemann, Tom Hanika (2022):
  FCA2VEC: Embedding Techniques for Formal Concept Analysis, in Complex Data Analytics with Formal Concept Analysis.
• Tobias Koopmann, Maximilian Stubbemann, Matthias Kapa, Michael Paris, Guido Buenstorf, Tom Hanika, Andreas Hotho, Robert Jaeschke, Gerd Stumme (2021):
  Proximity Dimensions and the Emergence of Collaboration: A HypTrails Study on German AI Research, in Scientometrics.
• Maximilian Stubbemann, Tom Hanika, Gerd Stumme (2022):
  Orometric Methods in Bounded Metric Data, in Advances in Intelligent Data Analysis XVIII.

Vorträge:

• Juli 2024: Time-Series Research at ISMLL, DataH Hannover
• September 2023: The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks, ECML/PKDD 2023
• September 2023: Intrinsic Dimensionality and Graph Learning, ISI Foundation Turin
• Janua 2023: Topological Data Analysis and Neural Networks, Dagstuhl Workshop on Concept Lattice Based Topological Data Analysis and Reasoning
• April 2022: LG4AV: Combining Language Models and Graph Neural Networks for Author Verification, Symposium on Intelligent Data Analysis 2022
• Juli 2021: Dimensionen von Nähe und ihr Einfluss auf die Entstehung von Kollaboration, ITeG Brown Bag Seminar
• April 2020: Orometric Methods in Bounded Metric Data, Symposium on Intelligent Data Analysis 2020

Forschungskommunikation:

• Podcast of the University of Kassel: How does ChatGpt work? (In German)
• Interview for the local magazine Mein Kassel (In German):
  Current state and future of language models and their implications four our lifes.
• External Lecturer at the Departement of Empirical Research on Schools and Teaching of the University of Kassel:
  ChatGPT et al. : Functionality, History and Consequences for Teaching (in German)

Begutachtungen:

• Programm Commitee: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 9-13 2024
• Subreviewer: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 19-23 2022
• Subreviewer: 20th International Semantic Web Conference, October 24-28 2021, Virtual Conference
• Subreviewer: 18th Extended Semantic Web Conference, June 6-10 2021, Hersonissos, Greece
• Subreviewer: 19th International Semantic Web Conference, November 1-6 2020, Virtual Conference
• Subreviewer: 25th International Conference on Conceptual Structures, September 18-21 2020, Bolzano, Italy
• Subreviewer: 24th European Conference on Artificial Intelligence, June 8-12 2020, Santiago de Compostela, Spain
• Subreviewer: 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 4 – 8, 2019, Anchorage, Alaska – USA
• Subreviewer: 15th International Conference on Formal Concept Analysis, June 25-28 2019 – Frankfurt, Germany