Gaussian Process Covariance Kernels for Pattern Discovery and Extrapolation
By Andrew Gordon Wilson, Ryan P. Adams. 2013
28 citations recorded by the source corpus.
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- Sergey Levine
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- Pieter Abbeel
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- Zoubin Ghahramani
- Abhinav Kumar Gupta
Citations in the corpus
- Manifold Gaussian Processes for regression (2014, methodology): “The first approach combines multiple standard covariance functions to form a new covariance function (Rasmussen and Williams, 2006; Wilson and Adams, 2013; Duvenaud et al., 2013).”
- Automatic Construction and Natural-Language Description of Nonparametric Regression Models (2014, background): “, 2010; Saatçi, Turner, and Rasmussen, 2010; Fox and Dunson, 2013), spectral mixture kernels (Wilson and Adams, 2013) (spectral kernels) and trend-cyclical-irregular models (e.”
- Structure Discovery in Nonparametric Regression through Compositional Kernel Search (2013, background): “Wilson & Adams (2013) derive kernels of the form SE × cos( x − x (cid:48) ), forming a basis for stationary kernels.”
- Statistical Model Criticism using Kernel Two Sample Tests (2015, background): “We now investigate the type of discrepancies found by this test by looking at the witness function (which can still be interpreted as the difference of kernel density estimates).”
- Student-t Processes as Alternatives to Gaussian Processes (2014, methodology): “The added flexibility of the TP is orthogonal to the choice of kernel, and could complement recent expressive closed form kernels [Wilson and Adams, 2013, Wilson et al., 2013] in future work.”
- Practical options for selecting data-driven or physics-based prognostics algorithms with reviews (2015, methodology): “The data-driven approaches are generally divided into two categories: (1) the artificial intelligence approaches that include neural network (NN) [21–23] and fuzzy logic [24,25]; and (2) the statistical approaches that include the Gaussian process (GP) regression [26,27], relevance/support vector ma”
- A temporal model of text periodicities using Gaussian Processes (2013, methodology): “This has been used in the GP framework by Wilson and Adams (2013).”