# Haut PDF High dimensional Bayesian computation

### High dimensional Bayesian computation

**Bayesian**statistics builds approximations of the posterior distribution either by sampling or by constructing tractable ...of

**Bayesian**stastics is the development of new methodology by ...

168

### Incremental bayesian network structure learning in high dimensional domains

**Bayesian**network structure learning. It could deal with

**high**

**dimensional**domains, where whole dataset is not completely available, but grows ...

8

### CrossCat: A fully Bayesian nonparametric method for analyzing heterogeneous, high dimensional data

**high**-

**dimensional**datasets with- out imposing restrictive or opaque modeling ...approximately

**Bayesian**inference in a hierarchical, nonparamet- ric model for data ...and

**Bayesian**net- ...

51

### Combining a Relaxed EM Algorithm with Occam's Razor for Bayesian Variable Selection in High-Dimensional Regression

**high**-

**dimensional**data spaces (Cand` es, 2014). In the context of linear regression, finding a parsimonious ...

38

### Class-specific Variable Selection in High-Dimensional Discriminant Analysis through Bayesian Sparsity

**high**performances for the classification and the great stability for the variable ...with

**high**-

**dimensional**data and for which an interpretation of the model is expected such as in all ...

21

### Convergence et spike and Slab Bayesian posterior distributions in some high dimensional models

**Bayesian**posterior distributions in some

**high**

**dimensional**models. The first main focus is the sparse Gaussian sequence model. An Empirical Bayes ...

161

### High-dimensional dependence modelling using Bayesian networks for the degradation of civil infrastructures and other applications

**high**-dimension deterioration problems using

**Bayesian**...of

**high**-

**dimensional**...that

**Bayesian**networks can be a versatile framework in which both statistical and ...

170

### Mixture of markov trees for bayesian network structure learning with small datasets in high dimensional space

**Bayesian**network structure learning in

**high**dimension ...Introduction

**Bayesian**network structure learning is NP-hard and existing algorithms are not scalable to very

**high**

**dimensional**...

11

### High-dimensional probability density estimation with randomized ensembles of tree structured bayesian networks

**Bayesian**networks aims at model- ing the joint density of a set of random variables from a random sample of joint observations of these variables (Cowell et ...for

**Bayesian**network structure learning are ...

9

### Uncertainty quantification on pareto fronts and high-dimensional strategies in bayesian optimization, with applications in multi-objective automotive design

**high**-dimension [ GBC + 14 ...fully

**Bayesian**approach, but then the predictive distribution has no more closed form expression, thus re- quiring the use of more computationally demanding techniques based ...

205

### High-Dimensional Bayesian Multi-Objective Optimization

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### High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm

**Bayesian**inference and machine learning. Under the assumption that U is continuously differentiable, ∇U is globally Lipschitz and U is strongly convex, ...

45

### Amount of information needed for model choice in Approximate Bayesian Computation

14

### Approximation of high-dimensional parametric PDEs

**dimensional**framework, and not covered in our paper, let us mention the following related works: (i) similar holomorphy and approximation results are established in [47, 48, 58] for specific type of PDEs ...

148

### Bayesian computation: a perspective on the current state, and sampling backwards and forwards

30

### HIV with contact-tracing: a case study in Approximate Bayesian Computation

**dimensional**summary statistics for ABC. When comparing ABC with the two different sets of statistics, we find that the point estimates of the parameters λ 1 , λ ...

20

### Approximation of high-dimensional parametric PDEs

**dimensional**framework, and not covered in our paper, let us mention the following related works: (i) similar holomorphy and approximation results are established in [47, 48, 58] for specific type of PDEs ...

148

### Bayesian multi-locus pattern selection and computation through reversible jump MCMC

33

### Anderson Localization in high dimensional lattices

197

### Acceleration Strategies of Markov Chain Monte Carlo for Bayesian Computation

143