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Gaussian processes for time-series modelling
Abstract
In this paper, we offer a gentle introduction to Gaussian processes for time-series data analysis. The conceptual framework of Bayesian modelling for time-series data is discussed and the foundations of Bayesian non-parametric modelling presented for Gaussian processes . We discuss how domain knowledge influences design of the Gaussian process models and provide case examples to highlight the approaches.
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Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
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Twitter reveals human mobility dynamics during the COVID-19 pandemic
Huang, X., Li, Z., Jiang, Y., Li, X., & Porter, D. (2020) · PLOS ONE · doi:10.1371/journal.pone.0241957 · Cited by 242
“To remove noises and reveal the general trend, we smooth the time series using a onedimensional Gaussian filter (σ = 2), one of the most popular filters widely applied in many temporal smoothing tasks [43, 44].”
MethodWang, Q.-A., Liu, Q., Ma, Z.-G., Wang, J.-F., Ni, Y.-Q., Ren, W.-X., & Wang, H.-B. (2024) · Measurement · doi:10.1016/j.measurement.2024.114509 · Cited by 65
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Hou, M., Xu, C., Li, Z., Liu, Y., Liu, W., Chen, E., & Bian, J. (2022) · Proceedings of the ACM Web Conference 2022 · doi:10.1145/3485447.3512056 · Cited by 59
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Metadata
- Authors
- Roberts, S., Osborne, M., Ebden, M., Reece, S., Gibson, N., & Aigrain, S.
- Venue
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Publisher
- The Royal Society
- Published
- 2013-02-13
- Volume
- 371
- Issue
- 1984
- Pages
- 20110550
- ISSN
- 1364-503X (ISSN-L)
- 1471-2962
- OpenAlex
- W2095654324
- Cited by
- 605
- References
- 1
- FWCI
- 8.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- royalsociety.org/journals/ethics-policies/data-sharing-mining/ (tdm)
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- Roberts, S., Osborne, M., Ebden, M., Reece, S., Gibson, N., & Aigrain, S. (2013). Gaussian processes for time-series modelling. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. https://doi.org/10.1098/rsta.2011.0550
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