My name is Martin Trapp, I’m a PhD candidate in machine learning. I have a particular interested in deep tractable probabilistic models, probabilistic programming and Bayesian nonparametrics for probabilistic modelling.

My thesis is supervised by Prof. Franz Pernkopf from the Graz University of Technology in cooperation with Asst. Prof. Robert Peharz from the Eindhoven University of Technology. Until 2019 I was also affiliated with the Austrian Research Institute for AI.

In my spare time, I’m working on the probabilistic programming language Turing.jl. Our goal is to provide an efficient, robust and intuitive probabilistic programming language for everyone.

To contact me, find me on Twitter or Github or drop me an e-mail.


  • [January 2020] Our paper on Deep Structured Mixtures of Gaussian Processes with Robert Peharz, Franz Pernkopf and Carl E. Rasmussen has been accepted at AISTATS.
  • [December 2019] Together with Antonio Vergari, I organised the first official NeurIPS social event on tractable probabilistic inference (T-PRIME).
  • [September 2019] Our paper on Bayesian Learning of Sum-Product Networks with Robert Peharz, Hong Ge, Franz Pernkopf and Zoubin Ghahramani has been accepted at NeurIPS (acceptance rate 21.2%).
  • [May 2019] Our paper on Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning with Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Xiaoting Shao, Kristian Kersting, and Zoubin Ghahramani has been accepted at UAI (acceptance rate 26.2%).
  • [June 2017] Our paper on Safe Semi-Supervised Learning of Sum-Product Networks with Tamas Madl, Robert Peharz, Franz Pernkopf, and Robert Trappl has been accepted at UAI (acceptance rate 31.0%).