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Gaussian random fields (Gaussian processes) are beautiful mathematical objects that are useful in a number of areas outside of pure mathematics. In machine learning, they are widely accepted as a model of choice in scenarios where decision making under uncertainty is required e.g. in black-box optimization and reinforcement learning. In this talk I will briefly overview Gaussian processes as a machine learning tool and discuss some of their real-world applications.


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