GPy is a Gaussian Process (GP) framework written in python, from the Sheffield machine learning group. Gaussian processes underpin range of modern machine learning algorithms. In GPy, we’ve used python to implement a range of machine learning algorithms based on GPs. GPy is available under the BSD 3-clause license.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Damianou, Andreas C.; Titsias, Michalis K.; Lawrence, Neil D.: Variational inference for latent variables and uncertain inputs in Gaussian processes (2016)
- Neumann, Marion; Huang, Shan; Marthaler, Daniel E.; Kersting, Kristian: pyGPS -- a python library for Gaussian process regression and classification (2015)