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Efficient Gaussian process regression for large datasets

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What this work says

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Voronoi Tessellation for Efficient Sampling in Gaussian Process-Based Robotic Motion Planning

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Performance Analysis of Machine Learning Algorithms for Energy Demand–Supply Prediction in Smart Grids

inferred← citeshttps://doi.org/10.3934/nhm.2024056openalex-snapshot

A data-driven reduced-order modeling approach for parameterized time-domain Maxwell's equations

inferred← citeshttps://doi.org/10.48550/arxiv.1303.1849openalex-snapshot

Revisiting the Nystrom Method for Improved Large-Scale Machine Learning

inferred← citeshttps://doi.org/10.48550/arxiv.1310.0732openalex-snapshot

Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction

inferred← citeshttps://doi.org/10.48550/arxiv.1312.1869openalex-snapshot

Parallel inversion of huge covariance matrices

inferred← citeshttps://doi.org/10.48550/arxiv.1401.8189openalex-snapshot

Generalized Gaussian Process Regression Model for Non-Gaussian Functional Data

inferred← citeshttps://doi.org/10.48550/arxiv.1402.5847openalex-snapshot

Modified Linear Projection for Large Spatial Data Sets

inferred← citeshttps://doi.org/10.48550/arxiv.1408.4660openalex-snapshot

Joint Hierarchical Gaussian Process Model with Application to Forecast in Medical Monitoring

inferred← citeshttps://doi.org/10.48550/arxiv.1411.7009openalex-snapshot

Additive Gaussian Process Regression

inferred← citeshttps://doi.org/10.48550/arxiv.1501.05427openalex-snapshot

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)

inferred← citeshttps://doi.org/10.48550/arxiv.1508.03387openalex-snapshot

Optimal approximating Markov chains for Bayesian inference

inferred← citeshttps://doi.org/10.48550/arxiv.1509.08999openalex-snapshot

Asynchronous Gibbs Sampling

inferred← citeshttps://doi.org/10.48550/arxiv.1608.02209openalex-snapshot

Bayesian Learning of Dynamic Multilayer Networks

inferred← citeshttps://doi.org/10.48550/arxiv.1609.02501openalex-snapshot

A Computationally Efficient Projection-Based Approach for Spatial Generalized Linear Mixed Models

inferred← citeshttps://doi.org/10.48550/arxiv.1611.02199openalex-snapshot

Inference for Additive Models in the Presence of Possibly Infinite Dimensional Nuisance Parameters

inferred← citeshttps://doi.org/10.48550/arxiv.1706.02040openalex-snapshot

Coupling and Decoupling to bound an approximating Markov Chain

inferred← citeshttps://doi.org/10.48550/arxiv.1706.04651openalex-snapshot

Spatial Regression and the Bayesian Filter

inferred← citeshttps://doi.org/10.48550/arxiv.1802.06308openalex-snapshot

Nonparametric Testing under Random Projection

inferred← citeshttps://doi.org/10.48550/arxiv.1908.08864openalex-snapshot

Sparse Additive Gaussian Process Regression

inferred← citeshttps://doi.org/10.48550/arxiv.1909.05440openalex-snapshot

Fast expectation-maximization algorithms for spatial generalized linear mixed models

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Fast increased fidelity approximate Gibbs samplers for Bayesian Gaussian process regression

inferred← citeshttps://doi.org/10.5194/gmd-12-955-2019openalex-snapshot

A new method (M 3 Fusion v1) for combining observations and multiple model output for an improved estimate of the global surface ozone distribution

inferred← citeshttps://doi.org/10.5555/2946645.3007022openalex-snapshot

Compressed Gaussian process for manifold regression

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Reduced-Dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models

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