Martin Trapp
Almost surely
Assistant Professor in Machine Learning & WASP Fellow
KTH Royal Institute of Technology
I am an Assistant Professor in Machine Learning at KTH Royal Institute of Technology, WASP fellow, and a member of the ELLIS society. Before joining KTH, I was an Academy of Finland postdoctoral researcher at Aalto University working with Arno Solin. My research is centred on making machine learning more #reliable by representing, quantifying, and reducing #uncertainty. I am particularly interested in #efficient and #principled approaches for large-scale machine learning models and AI agents.
See biography for more details.
Research Interests
- Tractable Models: Probabilistic circuits, neurosymbolics, and probabilistic inference.
- Bayesian Learning: Uncertainty in deep learning, approximate inference, and nonparametrics.
- Probabilistic Numerics: Low-precision regimes, surrogate uncertainty, and uncertainty propagation.
If you want to join my group, check the information for prospective PhD students, Postdocs, and MSc thesis students.
News & Updates
NeurIPS 2026!
[September 2026]Together with collegues we got two papers accepted at NeurIPS!
LOGML Project!
[July 2026]Together with Jiayi and six amazing students, we concluded our LOGML 2026 project on variational approximations for singular learning theory! Stay tuned for more.
ECCV Workshop proposal accepted!
[April 2026]Exciting news, we will organised a new version of our successfull workshop series on Uncertainty Quantification for Computer Vision at ECCV!