Anton Baumann

anton@antonbaumann.com - scholar - github - linkedin

machine learning researcher working on probabilistic methods, vision-language models and sample efficient reinforcement learning

Selected publications

  • Reinforcement Learning via Self-Distillation
    • Jonas Hübotter, Frederike Lübeck*, Lejs Behric*, Anton Baumann*, Marco Bagatella, Daniel Marta, Ido Hakimi, Idan Shenfeld, Thomas Kleine Buening, Carlos Guestrin, Andreas Krause
    • Under review; *equal second authorship.
    • Preprint - Project - GitHub
  • Post-hoc Probabilistic Vision-Language Models
    • Anton Baumann, Rui Li, Marcus Klasson, Santeri Mentu, Shyamgopal Karthik, Zeynep Akata, Arno Solin, Martin Trapp
    • ICLR 2026
    • Preprint - Project - GitHub
  • Probabilistic Active Few-Shot Learning in Vision-Language Models
    • Anton Baumann, Marcus Klasson, Rui Li, Arno Solin, Martin Trapp
    • NeurIPS 2024 BDU (spotlight & poster)
  • Probabilistic MIMO U-Net
    • Anton Baumann, Thomas Roßberg, Michael Schmitt.
    • ICCV 2023 UnCV (oral & poster)
    • Preprint - GitHub

Selected experience

Research roles and applied ML work across academia and industry.

  • Aalto University, Helsinki
    • Summer Research Intern, Machine Learning Research Group (May 2024 - May 2025)
      • Researched probabilistic ML for vision-language models in Arno Solin's lab.
  • Bundeswehr University, Munich
    • Research Assistant, Earth Observation Lab (Feb 2023 - May 2024)
      • Applied probabilistic ML and data fusion to remote sensing problems.
  • molab.ai, Munich
    • Data Scientist (Internship, then Part-time) (Aug 2022 - Feb 2023)
      • Implemented GNNs for chemical property prediction in PyTorch.
  • Ablacon GmbH, Munich
    • Researcher (Working Student), then Bachelor's Thesis (Mar 2020 - May 2022)
      • Extended Horn & Schunck optical flow for electrographic flow mapping.
      • Integrated the method into a prototype core product with a research engineering team.
  • Cliqz GmbH, Munich
    • Full-stack Developer (Working Student) (Sep 2017 - Jul 2019)
      • Developed logging/versioning system and JSON diff library in Go for privacy-first ad-tech infrastructure.

Education

  • ETH Zürich
    • Master's Thesis in Computer Science (Oct 2025 - Jun 2026 expected)
      • Meta test-time training for LLMs with joint supervision from Andreas Krause (ETH Zürich) and Zeynep Akata (TUM).
      • Day-to-day supervision by Jonas Hübotter.
  • KTH Stockholm
    • Exchange Semester (May 2024 - Feb 2025)
  • Technical University of Munich
    • M.Sc. Computer Science (Oct 2023 - Jun 2026 expected)
      • Ranked 1st/202 in official semester ranking (current GPA 1.2).
    • B.Sc. Computer Science, Minor in Mathematics (Oct 2018 - May 2022)
      • Thesis: "EGFX: Determining Optical Flow on Arbitrary Surfaces." (grade 1.0)
    • Early-study program in Computer Science (Oct 2016 - Oct 2017)