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Scoring Bayesian Networks with Informative, Causal and Associative Priors
Scoring Bayesian Networks Informative Causal Associative Priors
2012/11/26
A significant theoretical advantage of search-and-score methods for learning Bayesian Networks is that they can accept informative prior beliefs for each possible network, thus complementing the data....
A Bayesian Nonparametric Approach to Image Super-resolution
Bayesian nonparametrics factor analysis dictionary learning variational inference gibbs sampling stochastic optimization,image super-resolution.
2012/11/26
Super-resolution methods form high-resolution images from low-resolution images. In this paper, we develop a new Bayesian nonparametric model for super-resolution. Our method uses a beta-Bernoulli pro...
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
Polygenic Modeling Bayesian Sparse Linear Mixed Models
2012/11/23
Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide association studies. These two approaches ...
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are...
Nonparametric Bayesian methods for one-dimensional diffusion models: an overview of recent developments
Nonparametric Bayesian methods one-dimensional diffusion models overview of recent developments
2012/11/23
In this paper we review recently developed methods for nonparametric Bayesian inference for one-dimensional diffusion models. We discuss different possible prior distributions, computational issues, a...
Estimating Hidden Population Size using Respondent-Driven Sampling Data
Respondent-Driven Sampling Data Estimating Hidden Population Size
2012/11/23
Respondent-Driven Sampling (RDS) is an approach to sampling design and inference in hard-to-reach human populations. Typically, a sampling frame is not available, and population members are difficult ...
Bayesian inverse problems with non-conjugate priors
Rate of contraction posterior distribution nonparametric hypothesis testing.
2012/11/23
We investigate the frequentist posterior contraction rate of nonparametric Bayesian procedures in linear inverse problems in both the mildly and severely ill-posed cases. A theorem is proved in a gene...
Bayesian Analysis of Simple Random Densities
Bayesian nonparametrics Bayesian density estimation.
2012/11/23
A tractable nonparametric prior over densities is introduced which is closed under sampling and exhibits proper posterior asymptotics.
Bayes procedures for adaptive inference in nonparametric inverse problems
Bayes procedures adaptive inference nonparametric inverse problems
2012/11/22
We study empirical and hierarchical Bayes approaches to the problem of estimating an infinite-dimensional parameter in mildly ill-posed inverse problems. We consider a class of prior distributions ind...
A Bayesian Boosting Model
Bayesian Boosting Model
2012/11/22
We offer a novel view of AdaBoost in a statistical setting. We propose a Bayesian model for binary classification in which label noise is modeled hierarchically. Using variational inference to optimiz...
Default Bayesian Analysis for the Multivariate Ewens Distribution
Bayesian Analysis Multivariate Ewens Distribution
2012/11/22
We derive the Jeffreys prior for the parameter of the Multivariate Ewens Distribution and study some of its properties. In particular, we show that this prior is proper and has no finite moments. We a...
Bayesian interpretation of Generalized empirical likelihood by maximum entropy
Bayesian interpretation Generalized empirical likelihood maximum entropy
2012/3/1
We study a parametric estimation problem related to moment condition models. As an alternative to the generalized empirical likelihood (GEL) and the generalized method of moments (GMM), a Bayesian app...
Two-Photon Exchange Effect Studied with Neural Networks
Two-Photon Exchange Neural Networks
2011/7/21
The novel approach to the extraction of the two-photon exchange (TPE) correction from the elastic $ep$ scattering data is presented. The Bayesian framework for the neural networks is adapted. As the r...
Bound Dimers in Bilayers of Cold Polar Molecules
Bound Dimers Bilayers of Cold Polar Molecules
2011/3/3
The exploration of cold polar molecules in different geometries is a rapidly developing
experimental and theoretical pursuit. Recently, the implementation of optical lattices has enabled confinement ...
Experimental confirmation of chaotic phase synchronization in coupled time-delayed electronic circuits
chaotic phase synchronization coupled time-delayed electronic circuits
2010/12/28
We report the first experimental demonstration of chaotic phase synchronization (CPS) in unidirectionally coupled time-delay systems using electronic circuits. We have also implemented experimentally ...