Results 121 to 130 of about 157,640 (328)

Variational Bayesian Compressive Sensing with Equivalent Source Modeling for Sound Field Reconstruction

Sensors
While conventional Bayesian compressive sensing exploits signal sparsity for accurate sound field reconstruction from under-sampled measurements, its practicality is limited by high computational complexity and slow convergence.
Yue Xiao, Zhepu Chen, Haiyang Zhang, Chengping Zhong   +3 more
doaj   +1 more source

HIERARCHICAL BAYESIAN MODELING FOR SPATIAL TIME SERIES: AN ALTERNATIVE APPROACH TO SPATIAL SUR [PDF]

Despite the fact that the amount of datasets containing long economic time series with a spatial reference has significantly increased during the years, the presence of integrated techniques that aim to describe the temporal evolution of the series while
Yiannis Kamarianakis
core  

Estimation of fMRI responses related to epileptic discharges using Bayesian hierarchical modeling. [PDF]

Hum Brain Mapp, 2023
Cai Z, von Ellenrieder N, Koupparis A, Khoo HM, Ikemoto S, Tanaka M, Abdallah C, Rammal S, Dubeau F, Gotman J.   +9 more
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Baldur: Bayesian Hierarchical Modeling for Label-Free Proteomics with Gamma Regressing Mean-Variance Trends. [PDF]

Mol Cell Proteomics, 2023
Berg P, Popescu G.
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Multilevel Hierarchical Bayesian Modeling of Cross-National Factors in Vehicle Sales

Applied Sciences
SUVs (sport utility vehicles), as a car segment, have become a foundation within the automotive industry due to their versatility, which is used by a wide range of customers.
Monika Sukiennik, Jerzy Baranowski
doaj   +1 more source

Meta-Functional Benefit Transfer for Wetland Valuation: Making the Most of Small Samples [PDF]

This study applies functional Benefit Transfer via Meta-Regression Modeling to derive valuation estimates for wetlands in an actual policy setting of proposed groundwater transfers in Eastern Nevada.
Klaus Moeltner, Richard T. Woodward
core  

bakR: uncovering differential RNA synthesis and degradation kinetics transcriptome-wide with Bayesian hierarchical modeling. [PDF]

RNA, 2023
Vock IW, Simon MD.
europepmc   +1 more source