Results 71 to 80 of about 731,480 (301)
, 2018 This paper considers the problem of robust adaptive efficient estimating of a periodic function in a continuous time regression model with the dependent noises given by a general square integrable semimartingale with a conditionally Gaussian distribution.
Pchelintsev, Evgeny +1 more
core +1 more source
Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani +10 more
wiley +1 more source
Sparse Additive Gaussian Process Regression
, 2019 In this paper we introduce a novel model for Gaussian process (GP) regression in the fully Bayesian setting. Motivated by the ideas of sparsification, localization and Bayesian additive modeling, our model is built around a recursive partitioning (RP) scheme. Within each RP partition, a sparse GP (SGP) regression model is fitted.
Luo, Hengrui +2 more
openaire +3 more sources
Gaussian Process Regression for Binned Data [PDF]
, 2018 10 pages (+1 supp), 4 ...
Smith, M.T. +2 more
openaire +3 more sources
A Gaussian Process Robust Regression [PDF]
Progress of Theoretical Physics Supplement, 2005 A modified Gaussian process regression is proposed aiming at making regressors robust against outliers. The proposed method is based on U-loss, which is introduced as a natural extension of Kullback-Leibler divergence. The robustness is examined based on the influence function, and numerical experiments are conducted for contaminated data sets and it ...
Noboru Murata, Yusuke Kuroda
openaire +1 more source
Global Carbon Fluxes Using Multioutput Gaussian Processes Regression and MODIS Products
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe quantification of carbon fluxes (CFs) is crucial due to their role in the global carbon cycle having a direct impact on Earth's climate. In the last years, considerable efforts have been made to scale CFs from eddy covariance (EC) data to the ...
Manuel Campos-Taberner +6 more
doaj +1 more source
Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification [PDF]
, 1997 Gaussian processes are a natural way of defining prior distributions over functions of one or more input variables. In a simple nonparametric regression problem, where such a function gives the mean of a Gaussian distribution for an observed response, a ...
Neal, Radford M.
core +2 more sources
Associations of Rheumatoid Arthritis Disease Activity with Frailty Over Five Years of Follow‐up
Arthritis Care &Research, Accepted Article.Objective To evaluate whether rheumatoid arthritis (RA) disease activity is associated with frailty both in cross‐section and longitudinally. Methods Participants within the Veterans Affairs Rheumatoid Arthritis registry enrolled from 2003 to 2022 were included. The exposure was RA disease activity measured by Disease Activity Score in 28‐joints (DAS28)
Courtney N. Loecker +14 more
wiley +1 more source
Implicit Manifold Gaussian Process Regression
Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023 Gaussian process regression is widely used because of its ability to provide well-calibrated uncertainty estimates and handle small or sparse datasets. However, it struggles with high-dimensional data. One possible way to scale this technique to higher dimensions is to leverage the implicit low-dimensional manifold upon which the data actually lies, as
Fichera, Bernardo +3 more
openaire +2 more sources
, 2019 Bayesian Gaussian Process Optimization can be considered as a method of the determination of the model parameters, based on the experimental data.
Kovalenko, Vladimir
core +1 more source