Results 61 to 70 of about 1,248,103 (272)

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, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source

Polynomial Chaos Expanded Gaussian Process

Machine Learning and Knowledge Extraction
In complex and unknown processes, global models are fitted over the entire input domain but often tend to perform poorly whenever the response surface exhibits non-stationary behavior and varying smoothness.
Dominik Polke, Tim Kösters, Elmar Ahle, Dirk Söffker   +3 more
doaj   +1 more source

EigenGP: Gaussian Process Models with Adaptive Eigenfunctions [PDF]

, 2015
Gaussian processes (GPs) provide a nonparametric representation of functions. However, classical GP inference suffers from high computational cost for big data. In this paper, we propose a new Bayesian approach, EigenGP, that learns both basis dictionary
Peng, Hao, Qi, Yuan
core  

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, 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

Thermoreflectance Detection of Point Defects Resulting from Focused Ion Beam Milling

Advanced Engineering Materials, EarlyView.
Focused ion beam (FIB) milling is a common tool for nanoscale material processing, however irradiation damage, redeposition, and contamination can occur. We use several characterization tools to show FIB‐induced effects beyond 1 mm from the milled area.
Thomas W. Pfeifer, Eric R. Hoglund, Anton V. Ievlev, Patrick E. Hopkins   +3 more
wiley   +1 more source

Sparse On-Line Gaussian Processes [PDF]

Neural Computation, 2002
We develop an approach for sparse representations of gaussian process (GP) models (which are Bayesian types of kernel machines) in order to overcome their limitations for large data sets. The method is based on a combination of a Bayesian on-line algorithm, together with a sequential construction of a relevant subsample of the data that fully ...
Csato, Lehel, Opper, Manfred
openaire   +5 more sources

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

Prediction of the sodium absorption ratio using data-driven models: a case study in Iran

Geology, Ecology, and Landscapes, 2020
In this investigation, two data-driven models, i.e., Gaussian Process (GP) and Support Vector Machine (SVM), were used to predict the sodium absorption ratio (SAR) in three sub-watersheds (Khorramabad, Biranshahr, and Alashtar) in Iran.
Balraj Singh
doaj   +1 more source

Efficient learning variable impedance control for industrial robots [PDF]

Bulletin of the Polish Academy of Sciences: Technical Sciences, 2019
Compared with the robots, humans can learn to perform various contact tasks in unstructured environments by modulating arm impedance characteristics. In this article, we consider endowing this compliant ability to the industrial robots to effectively ...
C. Li, Z. Zhang, G. Xia, X. Xie, Q. Zhu
doaj   +1 more source

On the Lightweight Potential of Laser Additive Manufactured NiTi Triply Periodic Minimal Sheet Lattices

Advanced Engineering Materials, EarlyView.
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo, Shuo Qu, Shiming Gao, Xu Song   +3 more
wiley   +1 more source