Results 31 to 40 of about 851,390 (284)
On the Degeneracy between fσ8 Tension and Its Gaussian Process Forecasting
Universe, 2022 In this Article, we reconstruct the growth and evolution of the cosmic structure of the Universe using Markov chain Monte Carlo algorithms for Gaussian processes.
Mauricio Reyes, Celia Escamilla-Rivera
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Hitting times for Gaussian processes [PDF]
, 2007 We establish a general formula for the Laplace transform of the hitting times of a Gaussian process. Some consequences are derived, and particular cases like the fractional Brownian motion are discussed.Comment: Published in at http://dx.doi.org/10.1214 ...
Decreusefond, Laurent, Nualart, David
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Infinite Mixtures of Multivariate Gaussian Processes [PDF]
, 2013 This paper presents a new model called infinite mixtures of multivariate Gaussian processes, which can be used to learn vector-valued functions and applied to multitask learning.
Sun, Shiliang
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Gaussian Processes on Hypergraphs
CoRR, 2021 25 pages, 6 ...
Thomas Pinder +3 more
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Gaussian processes in ball bearing prognostics
Dyna, 2017 In this work, vibration analysis and Gaussian Processes techniques are used in useful life prognostics of ball bearings. The database is provided by The Prognostics Data Repository from NASA, and shows the failure evolution in ball bearings.
Juan Fernando López-López +2 more
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CoRR, 2011 Appearing in Neural Information Processing Systems ...
Duvenaud, D. +2 more
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CoRR, 2016 Gaussian process models are flexible, Bayesian non-parametric approaches to regression. Properties of multivariate Gaussians mean that they can be combined linearly in the manner of additive models and via a link function (like in generalized linear models) to handle non-Gaussian data. However, the link function formalism is restrictive, link functions
Alan D. Saul +3 more
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Modular Jump Gaussian Processes
Data Science in ScienceGaussian processes (GPs) furnish accurate nonlinear predictions with well-calibrated uncertainty. However, the typical GP setup has a built-in stationarity assumption, making it ill-suited for modeling data from processes with sudden changes, or “jumps ...
Anna R. Flowers +4 more
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Physical Review D, 2012 Gaussian processes provide a method for extracting cosmological information from observations without assuming a cosmological model. We carry out cosmography -- mapping the time evolution of the cosmic expansion -- in a model-independent manner using kinematic variables and a geometric probe of cosmology.
Shafieloo, Arman +2 more
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Integrated Gaussian Processes for Tracking
IEEE Open Journal of Signal ProcessingIn applications such as tracking and localisation, a dynamical model is typically specified for the modelling of an object's motion. An appealing alternative to the traditional parametric Markovian dynamical models is the Gaussian Process (GP ...
Fred Lydeard +2 more
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