Results 61 to 70 of about 110,828 (307)

Reinforcement learning with Gaussian process regression using variational free energy

Journal of Intelligent Systems, 2023
The essential part of existing reinforcement learning algorithms that use Gaussian process regression involves a complicated online Gaussian process regression algorithm.
Kameda Kiseki, Tanaka Fuyuhiko
doaj   +1 more source

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

Kinect posture reconstruction based on a local mixture of Gaussian process models

, 2016
Depth sensor based 3D human motion estimation hardware such as Kinect has made interactive applications more popular recently. However, it is still challenging to accurately recognize postures from a single depth camera due to the inherently noisy data ...
Shum, Hubert P.H., Shum, Hubert P. H., Leung, Howard, Liu, Zhiguang, Zhou, Liuyang   +4 more
core   +1 more source

UTILIZING GAUSSIAN PROCESS REGRESSION FOR NONLINEAR MAGNETIC SEPARATION PROCESS IDENTIFICATION

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
This paper presents a novel approach utilizing Gaussian Process Regression (GPR) to identify dynamic models with nonlinear parameters in magnetic separation processes.
Oleksandr Volovetskyi
doaj   +1 more source

Associations of Rheumatoid Arthritis Disease Activity With Frailty Over Five Years of Follow‐up

Arthritis Care &Research, EarlyView.
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 (VARA) registry enrolled from 2003 to 2022 were included.
Courtney N. Loecker, Yangyuna Yang, Punyasha Roul, Aaron Baraff, Myra S. Schmaderer, Lani Zimmerman, Kaleb Michaud, Namrata Singh, Grant W. Cannon, Gary Kunkel, Ted R. Mikuls, Ariela R. Orkaby, Joshua F. Baker, Bryant R. England, Katherine D. Wysham   +14 more
wiley   +1 more source

Nonlinear spectral unmixing of hyperspectral images using Gaussian processes [PDF]

, 2012
This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components ...
Altmann, Yoann, Altmann, Yoann; id_orcid, McLaughlin, Steve; id_orcid, Dobigeon, Nicolas, Tourneret, Jean-Yves, McLaughlin, Steve   +5 more
core   +1 more source

Gaussian process regression‐based load forecasting model

IET Generation, Transmission & Distribution
In this paper, Gaussian Process Regression (GPR)‐based models which use the Bayesian approach to regression analysis problem such as load forecasting (LF) are proposed.
Anamika Yadav, Rashmi Bareth, Matushree Kochar, Mohammad Pazoki, Ragab A. El Sehiemy   +4 more
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Derivative observations in Gaussian Process models of dynamic systems [PDF]

, 2002
Gaussian processes provide an approach to nonparametric modelling which allows a straightforward combination of function and derivative observations in an empirical model.
Murray-Smith , R., Leithead, WE, Leith, D, Solak, E., Leithead, W.E., Leithead , W., Rasmussen, C., ,, Rasmussen, C.E., Leith, D., Rasmussen, CE, Murray-Smith, R., Rasmusson, C., Leith, D.J., Solak, E, Murray Smith, R   +15 more
core  

Lithium-Ion Battery Prognostics with Hybrid Gaussian Process Function Regression

Energies, 2018
The accurate prognostics of lithium-ion battery state of health (SOH) and remaining useful life (RUL) have great significance for reducing the costs of maintenance.
Yu Peng, Yandong Hou, Yuchen Song, Jingyue Pang, Datong Liu   +4 more
doaj   +1 more source