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Nonstationary nonseparable random fields
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Wang, Kangrui, Hamelijnck, Oliver, Damoulas, Theodoros and Steel, Mark F. J. (2020) Nonstationary nonseparable random fields. In: 37th International Conference on Machine Learning, Remote, 12-18 Jul 2020 (In Press)
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WRAP-Nonstationary-nonseparable-random-fields-Damoulas-2020.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (632Kb) |
Abstract
We describe a framework for constructing nonsta- tionary nonseparable random fields that are based on an infinite mixture of convolved stochastic processes. When the mixing process is station- ary but the convolution function is nonstationary we arrive at nonseparable kernels with constant non-separability that are available in closed form. When the mixing is nonstationary and the convolu- tion function is stationary we arrive at nonsepara- ble random fields that have varying nonseparabil- ity and better preserve local structure. These fields have natural interpretations through the spectral representation of stochastic differential equations (SDEs) and are demonstrated on a range of syn- thetic benchmarks and spatio-temporal applica- tions in geostatistics and machine learning. We show how a single Gaussian process (GP) with these random fields can computationally and sta- tistically outperform both separable and existing nonstationary nonseparable approaches such as treed GPs and deep GP constructions.
| Item Type: | Conference Item (Paper) | ||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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| Divisions: | Faculty of Science > Computer Science Faculty of Science > Statistics |
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| Official Date: | 2020 | ||||||
| Dates: |
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| Date of first compliant deposit: | 9 June 2020 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | In Press | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | 37th International Conference on Machine Learning | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Remote | ||||||
| Date(s) of Event: | 12-18 Jul 2020 | ||||||
| Related URLs: |
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