搜索结果: 1-15 共查到“Bayesian Inference”相关记录43条 . 查询时间(0.046 秒)
Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens
egg production fertility genetic correlation hatchability heritability
2018/11/23
This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inf...
中国地质大学科学技术发展院肖异凡(博士生),何卫红等地球科学学院 Earth-Science Reviews，Available online 16 Feb 2018， Low-latitudinal standard Permian radiolarian biostratigraphy for multiple purposes with Unitary Association, Graphic Correlation, and Bayesian inference methods
低纬地区的标准二叠纪放射虫生物地层-单元组合法
2021/10/21
2018年2月，中国地质大学地球科学学院和生物地质与环境地质国家重点实验室何卫红教授团队，联合日本学者铃木纪毅博士，在国际地学领域著名期刊《Earth-Science Reviews》上在线发表题为“Low-latitudinal standard Permian radiolarian biostratigraphy for multiple purposes with Unitary Asso...
Prediction,Bayesian inference and feedback in speech recognition
Speech recognition Bayesian inference feedback prediction
2016/5/3
Speech perception involves prediction, but how is that prediction implemented? In cognitive models prediction has often been taken to imply that there is feedback of activation from lexical to pre-lex...
Bayesian Inference and the Parametric Bootstrap。
Connectionist models and Bayesian inference.
Solving the Problem of Cascading Errors:Approximate Bayesian Inference for Linguistic Annotation Pipelines
Problem of Cascading Errors Approximate Bayesian Inference Linguistic Annotation Pipelines
2015/6/12
The end-to-end performance of natural language processing systems for compound tasks, such as question answering and textual entailment, is often hampered by use of a greedy 1-best pipeline architectu...
Bayesian inference with latent variables.
Informative Bayesian inference for the skew-normal distribution
Bayesian inference Gibbs sampling Markov Chain Monte Carlo Multivariate skew-normal distribution Stochastic representation of the skew-normal Uni
2013/6/14
Motivated by the analysis of the distribution of university grades, which is usually asymmetric, we discuss two informative priors for the shape parameter of the skew-normal distribution, showing that...
Mean field variational Bayesian inference for support vector machine classification
Approximate Bayesian inference variable selection missing data mixed model Markov chain Monte Carlo
2013/6/14
A mean field variational Bayes approach to support vector machines (SVMs) using the latent variable representation on Polson & Scott (2012) is presented. This representation allows circumvention of ma...
A Markov Model of Machine Translation using Non-parametric Bayesian Inference
Markov Model Machine Translation Non-parametric Bayesian Inference
2014/3/20
Most modern machine translation systems use phrase pairs as translation units, allowing for accurate modelling of phraseinternal translation and reordering. However phrase-based approaches are much le...
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
A Fast Iterative Bayesian Inference Algorithm Sparse Channel Estimation
2013/4/27
In this paper, we present a Bayesian channel estimation algorithm for multicarrier receivers based on pilot symbol observations. The inherent sparse nature of wireless multipath channels is exploited ...
Bayesian inference for nonlinear structural time series models
DSGEmodel Multi-modal Partially adapted particle flter State space
2012/11/21
This article discusses a partially adapted particle filter for estimating the likelihood of a nonlinear structural econometric state space models whose state transition density cannot be expressed in ...
Bayesian inference on dependence in multivariate longitudinal data
Cholesky decomposition covariance matrix moment-matching oxidative stress random effects shrinkage prior.
2012/9/17
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging
due to the dimensionality involved. By concate...
Robust Bayesian inference of networks using Dirichlet t-distributions
Bayesian inference Dirichlet process graphical model Markov chain Monte Carlo t-distribution.
2012/9/18
Bayesian graphical modeling provides an appealing way to obtain uncertainty esti-mates when inferring network structures, and much recent progress has been made for Gaussian models. These models have ...
Bayesian Inference and Prediction of Burr Type XII Distribution for Progressive First Failure Censored Sampling
Burr Type XII Distribution Progressive First-Failure Censored Sample Bayesian Estimations Gibbs Sampling Markov Chain Monte Carlo Posterior Predictive Density
2013/1/28
This paper deals with Bayesian inference and prediction problems of the Burr type XII distribution based on progressive first failure censored data. We consider the Bayesian inference under a squared ...