Results 121 to 130 of about 2,475,679 (305)

Ensemble Modeling with a Bayesian Maximal Information Coefficient-Based Model of Bayesian Predictions on Uncertainty Data

Information
Uncertainty presents unfamiliar circumstances or incomplete information that may be difficult to handle with a single model of a traditional machine learning algorithm.
Tisinee Surapunt, Shuliang Wang
doaj   +1 more source

Nanozymes Integrated Biochips Toward Smart Detection System

Advanced Science, EarlyView.
This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen, Wang Zheng, Zhihui Zhang, Shenping Yu, Xinxin Hang, Han Wu, Xiao‐Wei Xiang, Wei Mu, Yanli Jiao, Zaizai Dong, Lingqian Chang   +10 more
wiley   +1 more source

A novel caputo fractional model for english language learning: Analysis and simulation with bayesian regularization approach

MethodsX
In this paper, a new Caputo discrete fractional model is introduced to capture the dynamics of English language learning. This model creates a strong foundation for examining language acquisition behaviors by including the learning process within the ...
Maria, Aqsa Zafar Abbasi, Muhammad Asif Zahoor Raja, Kottakkaran Sooppy Nisar, Muhammad Shoaib   +4 more
doaj   +1 more source

Bayesian model updating via streamlined Bayesian active learning cubature

This paper proposes a novel Bayesian active learning method for Bayesian model updating, which is termed as "Streamlined Bayesian Active Learning Cubature" (SBALC). The core idea is to approximate the log-likelihood function using Gaussian process (GP) regression in a streamlined Bayesian active learning way.
Li, Pei-Pei, Dang, Chao, Acevedo, Cristóbal H., Valdebenito, Marcos A., Faes, Matthias G. R.   +4 more
openaire   +2 more sources

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

Advanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang, Bowen Fu, Chuanchao Zhang, Xiaoping Liu   +3 more
wiley   +1 more source

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

Advanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao, Gaiqin Liu, Jingyi Xia, Runle Chen, Tong Wang, Xiaoling Yang, Ruiling Fang, Yanhong Luo, Ping Zeng, Hongmei Yu, Yanbo Zhang, Yuehua Cui   +11 more
wiley   +1 more source

The Bayesian iterated learning model

Abstract The Bayesian iterated learning model (BILM) provides a computational and mathematical solution to the problem of how learners’ biases causally affect the evolution of culturally transmitted information. Early simulations of language evolution found that learning biases could affect the evolution of linguistic structure, however,
openaire   +1 more source

A Subset of Pro‐inflammatory CXCL10+ LILRB2+ Macrophages Derives From Recipient Monocytes and Drives Renal Allograft Rejection

Advanced Science, EarlyView.
This study uncovers a recipient‐derived monocyte‐to‐macrophage trajectory that drives inflammation during kidney transplant rejection. Using over 150 000 single‐cell profiles and more than 850 biopsies, the authors identify CXCL10+ macrophages as key predictors of graft loss.
Alexis Varin, Jovanne Palvair, Lennie Messager, Jamal Bamoulid, Jasper Callemeyn, Mélanie Chaintreuil, Ludivine Dal Zuffo, Didier Ducloux, Imane Farhat, Mathieu Legendre, Laurent Martin, Florian Renosi, Xavier Roussel, Thibaut Vaulet, Maarten Naesens, Claire Tinel, Baptiste Lamarthée   +16 more
wiley   +1 more source

Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches

Scientific Reports
Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. However, in high-stakes and complex domains like healthcare, the opaque nature of these models makes it ...
Mohsin Akram, Muhammad Adnan, Syed Farooq Ali, Jameel Ahmad, Amr Yousef, Tagrid Abdullah N. Alshalali, Zaffar Ahmed Shaikh   +6 more
doaj   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source