Results 11 to 20 of about 844,595 (275)
Compositionally-warped Gaussian processes [PDF]
Neural Networks, 2019 Accepted at Elsevier Neural Networks, DOI added and author order ...
Gonzalo Rios, Felipe Tobar
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Gaussian process hydrodynamics
Applied Mathematics and Mechanics, 2023 AbstractWe present a Gaussian process (GP) approach, called Gaussian process hydrodynamics (GPH) for approximating the solution to the Euler and Navier-Stokes (NS) equations. Similar to smoothed particle hydrodynamics (SPH), GPH is a Lagrangian particle-based approach that involves the tracking of a finite number of particles transported by a flow ...
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Recurrent Gaussian processes [PDF]
, 2015 Published as a conference paper at ICLR 2016.
Mattos, C.L.C. +5 more
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Gaussian Processes and Gaussian Measures
The Annals of Mathematical Statistics, 1972 The subject of this paper is the study of the correspondence between Gaussian processes with paths in linear function spaces and Gaussian measures on function spaces. For the function spaces $C(I), C^n\lbrack a, b\rbrack, AC\lbrack a, b\rbrack$ and $L_2(T, \mathscr{A}, \nu)$ it is shown that if a Gaussian process has paths in these spaces then it ...
Rajput, Balram S., Cambanis, Stamatis
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Distributed Gaussian Processes [PDF]
, 2015 To scale Gaussian processes (GPs) to large data sets we introduce the robust Bayesian Committee Machine (rBCM), a practical and scalable product-of-experts model for large-scale distributed GP regression. Unlike state-of-the-art sparse GP approximations,
Deisenroth, Marc Peter, Ng, Jun Wei
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CONVEX BODIES AND GAUSSIAN PROCESSES
Image Analysis and Stereology, 2011 For several decades, the topics of the title have had a fruitful interaction. This survey will describe some of these connections, including the GB/GC classification of convex bodies, Ito-Nisio singularities from a geometric viewpoint, Gaussian ...
Richard A Vitale
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HYPERPARAMETER OPTIMIZATION BASED ON A PRIORI AND A POSTERIORI KNOWLEDGE ABOUT CLASSIFICATION PROBLEM [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2020 Subject of Research. The paper deals with Bayesian method for hyperparameter optimization of algorithms, used in machine learning for classification problems.
Valentina S. Smirnova +3 more
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Finite range Decomposition of Gaussian Processes [PDF]
, 2003 Let $\D$ be the finite difference Laplacian associated to the lattice $\bZ^{d}$. For dimension $d\ge 3$, $a\ge 0$ and $L$ a sufficiently large positive dyadic integer, we prove that the integral kernel of the resolvent $G^{a}:=(a-\D)^{-1}$ can be ...
Brydges, David C. +2 more
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Design Space Exploration of Turbulent Multiphase Flows Using Machine Learning-Based Surrogate Model
Energies, 2020 This study focuses on establishing a surrogate model based on machine learning techniques to predict the time-averaged spatially distributed behaviors of vaporizing liquid jets in turbulent air crossflow for momentum flux ratios between 5 and 120.
Himakar Ganti +2 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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