Add topic "Gaussian process" Accepted
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Add Gaussian processes for time-series modelling
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- Gaussian processes for time-series modelling
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- Paper
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- 2013-02-13
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- 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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- https://royalsocietypublishing.org/doi/10.1098/rsta.2011.0550
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- ISSN: 1364-503X, 1471-2962
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Add Gaussian process
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- Gaussian process
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- In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that every finite collection of those random variables has a multivariate normal distribution, i.e. every finite linear combination of them is normally distributed. The distribution of a Gaussian process is the joint distribution of all those (infinitely many) random variables, and as such, it is a distribution over functions with a continuous domain, e.g. time or space. A machine-learning algorithm that involves a Gaussian process uses lazy learning and a measure of the similarity between points (the kernel function) to predict the value for an unseen point from training data. The prediction is not just an estimate for that point, but also has uncertainty information—it is a one-dimensional Gaussian distribution.
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- https://en.wikipedia.org/?curid=302944
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Add Gaussian process treated in Gaussian processes for time-series modelling
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