Martin Trapp



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    Personal profile

    Artistic and research interests

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

    Artistic and research interests

    My research interests focus on probabilistic machine learning approaches in which the exploitation of structural properties (e.g., symmetries or conditional independencies) enables (exact and) efficient computations. Moreover, I am intrigued by prior specification and approximate inference in Bayesian deep learning, and approximate inference in Bayesian nonparametrics (Gaussian processes and priors on random partitions).

    In addition to my research, I’m part of the open-source project Turing.jl, which aims to provide a robust general-purpose probabilistic programming language for all branches of science. 

    Expertise related to UN Sustainable Development Goals

    In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

    • SDG 7 - Affordable and Clean Energy

    Education/Academic qualification

    PhD, Graz University of Technology

    Nov 2015Aug 2020


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