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Secondmind's research activities to make Gaussian Processes industry proof

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Secondmind is developing a cloud based engine calibration tool based on Gaussian process models and Bayesian optimisation. In this talk we present an industry point of view of the challenges associated with Gaussian process models in general, and more precisely with sparse variational gaussian process models. We also present some simple modelling tips that can make a big practical difference, and give an overview of the research we have recently conducted to overcome what we see as the most challenging limitations of GP models. More specifically we will review some of Secondmind’s contributions to make GP models more computationally efficient and more versatile.

This talk is part of the Machine Learning Reading Group @ CUED series.

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