AI Seminar: Deep probabilistic programming and the protein folding problem – University of Copenhagen

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Thomas Hamelryck is associate professor at the University of Copenhagen. His main interests are Bayesian machine learning, including deep probabilistic programming, and the protein folding problem. ...to formulate a suitable probabilistic model for a given data set and 3. Such an approach has been made possible by recent breakthroughs in automatic inference (including advanced sampling methods and variational inference) and numerical computing (including GPU-savvy numerical software such as PyTorch and TensorFlow). I will outline what probabilistic programming and deep probabilistic programming are about and discuss their relevance to an important, timely paradigm challenge - the protein folding problem.

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