Martin Trapp

Postdoctoral Researcher
Postdoctoral Researcher
T313 Dept. Computer Science

Probabilistic Machine Learning, Probabilistic Circuits, Probabilistic Programming, Bayesian nonparametrics

Full researcher profile

Contact information

Phone number

Areas of expertise

113 Computer and information sciences, Computational data analysis

Honors and awards

Positive Semi-Definite Circuits

HIIT short term project
Granted funding (public project funding) Department of Computer Science Nov 2022

Research groups

  • Professorship Solin A., Postdoctoral Researcher


Anomaly Detection Using Generative Models and Sum-Product Networks in Mammography Scans

Marc Dietrichstein, David Major, Martin Trapp, Maria Wimmer, Dimitrios Lenis, Philip Winter, Astrid Berg, Theresa Neubauer, Katja Bühler 2022 Deep Generative Models - 2nd MICCAI Workshop, DGM4MICCAI 2022, Held in Conjunction with MICCAI 2022, Proceedings

A Hardware Perspective to Evaluating Probabilistic Circuits

Jelin Leslin, Antti Hyttinen, Karthekeyan Periasamy, Lingyun Yao, Martin Trapp, Martin Andraud 2022

Uncertainty-guided source-free domain adaptation

Subhankar Roy, Martin Trapp, Andrea Pilzer, Juho Kannala, Nicu Sebe, Elisa Ricci, Arno Solin 2022 Computer Vision – ECCV 2022

Towards Coreset Learning in Probabilistic Circuits

Martin Trapp, Steven Lang, Aastha Shah, Martin Mundt, Kristian Kersting, Arno Solin 2022

Periodic Activation Functions Induce Stationarity

Lassi Meronen, Martin Trapp, Arno Solin 2021 Advances in Neural Information Processing Systems 34 (NeurIPS 2021)

Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression

Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, Kristian Kersting 2021 Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence