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  • University of British Columbia
  • Vancouver

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tueboesen/README.md

Hi! I'm Tue Boesen.

I am a machine learning scientist and have previously worked as: software developer, researcher, project lead, and technical advisor/consultant on various projects. I have a solid foundation in: physics, mathematics, data science, and high-performance-computing. I am familiar with programming best practices and generating production-ready code. Within machine learning, I have specialized in physics-informed and graph neural networks, but I have experience with most areas of deep learning, and I have applied machine learning in many different fields.

My CV can be found here.

To get in contact with me, please send an email to [email protected].

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  1. Sparse-iterative-parallel-linear-solver Sparse-iterative-parallel-linear-solver Public

    This is a sparse iterative parallel linear solver I developed during my PhD. The solver works by splitting the matrix into blocks which are then solved in parallel. The solver assumes the input mat…

    Fortran 14

  2. SSL-clustering SSL-clustering Public

    A simple example of semi-supervised clustering with constraint.

    MATLAB 2 1

  3. A-Optimal-Active-Learning A-Optimal-Active-Learning Public

    A-optimal active learning framework.

    Python 2

  4. Boardgame_AI Boardgame_AI Public

    A general framework made for training neural networks on boardgames.

    Python 2

  5. multi-body-pendulum multi-body-pendulum Public

    A module for simulating multi-body pendulums

    Python 3

  6. Constrained-Neural-Networks Constrained-Neural-Networks Public

    This project provides a novel combination of the field of differential algebraic equations and deep neural networks, and this combination enables us to add constraints to neural networks. We explor…

    Python 3