Results 121 to 130 of about 128,009 (300)

"Minimax Empirical Bayes Ridge-Principal Component Regression Estimators" [PDF]

In this paper, we consider the problem of estimating the regression parameters in a multiple linear regression model with design matrix A when the multicollinearity is present.
Tatsuya Kubokawa, M. S. Srivastava
core  

Bayes' Method for Bookies

The Annals of Mathematical Statistics, 1969
Freedman, David A., Purves, Roger A.
openaire   +3 more sources

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

PRMT1‐Mediated LDHA Methylation Drives STAT3 Lactylation to Orchestrate Intestinal Inflammation and Tumorigenesis

Advanced Science, EarlyView.
This study identifies an immunometabolic axis wherein SAM‐driven PRMT1 methylates LDHA, enhancing its activity. The resultant lactate induces STAT3 K709 lactylation, which stabilizes an active conformation to promote STAT3 phosphorylation and IL‐10 expression.
Hui Wang, Mengyu Zhang, Weipeng Gong, Jiaxuan Wu, Junping Zhang, Wenxiu Zhang, Yue Liu, Kui Wang, Canhua Huang, Jun Zhou, Sijin Wu, Yan Li, Tianliang Li   +12 more
wiley   +1 more source

Pendekatan Metode Ensemble Learning untuk Prakiraan Cuaca menggunakan Soft Voting Classifier

Journal of Applied Computer Science and Technology
Weather conditions are one of the crucial factors that need attention. Changes in weather conditions significantly impact various activities. Weather condition changes are determined by numerous factors, often occurring within a relatively short period ...
Steven Joses, Donata Yulvida, Siti Rochimah   +2 more
doaj   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Engineering Approaches to Modify Immunomodulatory Functions of Mesenchymal Stromal Cells (MSCs): Tissue Regeneration and Clinical Application

Advanced Science, EarlyView.
Mesenchymal stromal cells (MSCs) show promise for treating immune‐related disorders through immunomodulation and tissue regeneration. This review gives a brief overview of current clinical approval of MSC therapies. It also discussed how bioengineering, including genetic modification, biomaterial delivery, extracellular vesicles, and iPSC‐derived MSCs,
Sichen Yang, Kejia Li, Ning Wang, Zhen Li, Zhiyong Zhang, Rocky S. Tuan, Yangzi Jiang   +6 more
wiley   +1 more source

EbayesThresh: R Programs for Empirical Bayes Thresholding [PDF]

Suppose that a sequence of unknown parameters is observed sub ject to independent Gaussian noise. The EbayesThresh package in the S language implements a class of Empirical Bayes thresholding methods that can take advantage of possible sparsity in the ...
Iain Johnstone, Bernard W. Silverman
core   +1 more source

Sample-based Search Methods for Bayes-Adaptive Planning [PDF]

, 2015
A fundamental issue for control is acting in the face of uncertainty about the environment. Amongst other things, this induces a trade-off between exploration and exploitation.
Guez, AG
core  

Data-Driven Yield Estimation and Maximization Using Bayesian Optimization Under Uncertainty

Applied Sciences
In this paper, we propose a novel method which utilizes samples of measured product quality characteristics to efficiently estimate the probabilities of those quality characteristics being within the desired specifications and, consequently, the process ...
Kei Sano, Daiki Kawahito, Yukiya Saito, Hironori Moki, Dragan Djurdjanovic   +4 more
doaj   +1 more source