Results 111 to 120 of about 147,580 (306)

A Bayesian Hyperparameter Inference for Radon-Transformed Image Reconstruction

International Journal of Biomedical Imaging, 2011
We develop a hyperparameter inference method for image reconstruction from Radon transform which often appears in the computed tomography, in the manner of Bayesian inference.
Hayaru Shouno, Madomi Yamasaki, Masato Okada   +2 more
doaj   +1 more source

Bayesian and Non-Bayesian Approaches to Scientific Modeling and Inference in Economics and Econometrics [PDF]

After brief remarks on the history of modeling and inference techniques in economics and econometrics , attention is focused on the emergence of economic science in the 20th century. First, the broad objectives of science and the Pearson-Jeffreys' "unity
Arnold Zellner
core  

Approximate Bayesian inference for doubly robust estimation [PDF]

, 2015
Doubly robust estimators are typically constructed by combining outcome regression and propensity score models to satisfy moment restrictions that ensure consistent estimation of causal quantities provided at least one of the component models is ...
McCoy, EJ, Graham, DJ, Stephens, DA
core   +1 more source

Integrated Single‐Cell and Spatial Analysis Reveals a Metabolic‐Immune Axis Driving Aortic Dissection

Advanced Science, EarlyView.
Single‐cell and spatial profiling of 110 human thoracic aortic samples reveals a stromal–immune circuit driving aortic dissection. An elastin‐rich fibroblast subset is depleted with age and markedly reduced in disease, weakening aortic wall integrity.
Jing Tao, Huanjie Yang, Jiahui Yong, Xueting Chen, Qiang Zhao, Xueli Wu, Lei Yan, Li Pang, Fan Luo, Mengjun Yu, Shanshan Pan, Deyang Li, Rouxi Chen, Juan Wang, Zhensheng Dong, Fan Yang, Yue Wang, Yang Chen, Hongjian Zheng, Zhimin Yang, Zijie Wang, Karsten Kristiansen, Hui Peng, Xiaodong Fang, Juan Shen, Yining Yang   +25 more
wiley   +1 more source

Using simulation methods for Bayesian econometric models: inference, development, and communication [PDF]

This paper surveys the fundamental principles of subjective Bayesian inference in econometrics and the implementation of those principles using posterior simulation methods.
John Geweke
core  

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Seeing the wood for the trees : philosophical aspects of classical, Bayesian and likelihood approaches in statistical inference and some implications for phylogenetic analysis

, 2015
The three main approaches in statistical inference – classical statistics, Bayesian and likelihood – are in current use in phylogeny research. The three approaches are discussed and compared, with particular emphasis on theoretical properties illustrated
Barker, Daniel
core   +1 more source

Bayesian Nonparametric Inference for a Multivariate Copula Function [PDF]

, 2014
The paper presents a general Bayesian nonparametric approach for estimating a high dimensional copula. We first introduce the skew-normal copula, which we then extend to an infinite mixture model.
Wu, Juan, Wang, Xue, Walker, Stephen G.
core   +1 more source

Machine Learning‐Driven Prediction of Microplastic Aging Processes and Environmental Risk Assessment Across Multi‐Media Systems

Advanced Science, EarlyView.
This perspective proposes a cohesive machine learning strategy to decode microplastic aging. It advocates for Federated Learning to dismantle global data silos and introduces the TRACE framework (TRansport, Aging, Corona, Ecotoxicity). By integrating physics‐informed modeling with causal discovery, this approach bridges the laboratory‐field gap to ...
Yaping Lyu, Xinran Qiu, Xing Li, Tianhuan Yang, Xuetao Guo, Hao Qiu, Peng Zhang   +6 more
wiley   +1 more source