
hdi
 Referenced in 26 articles
[sw22818]
 HighDimensional Inference. Implementation of multiple approaches to perform inference in highdimensional models...

EigenPrism
 Referenced in 15 articles
[sw21947]
 EigenPrism: inference for high dimensional signaltonoise ratios. Consider the following three important problems ... statistical inference: constructing confidence intervals for the error of a high dimensional (p>n) regression ... performing inference on the l 2 norm of the signal in high dimensional linear regression...

ROCKET
 Referenced in 13 articles
[sw30016]
 variables is of fundamental importance in highdimensional statistics, with numerous applications in biological ... focus on inference for edge parameters in a highdimensional transelliptical model, which generalizes Gaussian ... normality of ROCKET in an ultra highdimensional setting under mild assumptions, without relying ... Gaussian models in terms of achieving accurate inference on simulated data. We also compare...

VBayesLab
 Referenced in 5 articles
[sw41752]
 models. Efficient computational methods for highdimensional Bayesian inference are developed using Gaussian variational approximation ... Bayesian inference approach lead to a regression and classification method that has a high prediction...

hdm
 Referenced in 7 articles
[sw21313]
 selected highdimensional statistical and econometric methods for estimation and inference. Efficient estimators and uniformly ... structural parameters are provided which appear in highdimensional approximately sparse models. Including functions ... highdimensional setting. Moreover, the methods enable valid postselection inference and rely...

SIHR
 Referenced in 2 articles
[sw39919]
 package SIHR: Statistical Inference in High Dimensional Regression. Inference procedures in the highdimensional setting...

FFJORD
 Referenced in 9 articles
[sw34244]
 approach on highdimensional density estimation, image generation, and variational inference, achieving the state...

DREAM
 Referenced in 9 articles
[sw24746]
 unknown parameter values, x are subject to inference using the data Y ¿ . Unfortunately, for complex ... models the posterior distribution is often high dimensional and analytically intractable, and sampling methods ... 2008a, 2009a) and used for Bayesian inference in fields ranging from physics, chemistry and engineering ... sampling problems involving (among others) bimodality, highdimensionality, summary statistics, bounded parameter spaces, dynamic simulation...

GANomaly
 Referenced in 5 articles
[sw41240]
 learns the generation of highdimensional image space and the inference of latent space. Employing...

PersistenceImages
 Referenced in 40 articles
[sw41418]
 convert a PD to a finitedimensional vector representation which we call a persistence image ... features containing discriminating topological information. Finally, high accuracy inference of parameter values from the dynamic...

polychord
 Referenced in 12 articles
[sw25768]
 PolyChord is a Bayesian inference tool for the simultaneous calculation of evidences and sampling ... MultiNest. It performs well on moderately high dimensional ( 100s D) posterior distributions, and can cope...

hierinf
 Referenced in 4 articles
[sw33471]
 hierarchical inference for one or multiple studies / data sets based on highdimensional multivariate (generalised...

PyDREAM
 Referenced in 1 article
[sw34672]
 PyDREAM: highdimensional parameter inference for biological models in python. : Biological models contain many parameters ... exhibit slow or premature convergence in highdimensional search spaces. Here, we present PyDREAM ... advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPUintensive biological...

GGMselect
 Referenced in 9 articles
[sw10347]
 Graph selection with GGMselect. Applications on inference of biological networks have raised a strong interest ... problem of graph estimation in highdimensional Gaussian graphical models. To handle this problem...

ADMB
 Referenced in 17 articles
[sw07416]
 builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Many criteria ... framework based on automatic differentiation, aimed at highly nonlinear models with a large number ... using AD are computational efficiency and high numerical accuracy, both crucial in many practical problems ... generic implementation of Laplace approximation of highdimensional integrals for use in latent variable models...

EEBoost
 Referenced in 1 article
[sw26353]
 which can be applied in highdimensional settings where inference for lowdimensional parameters would...

HDTD
 Referenced in 2 articles
[sw38988]
 Statistical Inference about the Mean Matrix and the Covariance Matrices in HighDimensional Transposable Data ... called highdimensional transposable data. The HDTD package provides functions for conducting statistical inference...

RCAL
 Referenced in 2 articles
[sw33473]
 estimation for causal inference and missingdata problems with highdimensional data, based...

TempoGAN
 Referenced in 10 articles
[sw42570]
 designed for the inference of threedimensional volumetric data, our model generates consistent and detailed ... generator is able to infer more realistic highresolution details by using additional physical quantities...

mvPot
 Referenced in 1 article
[sw42605]
 Extreme Events. Tools for highdimensional peaksoverthreshold inference and simulation of spatial extremal...