
AMIDST
 Referenced in 5 articles
[sw21741]
 Scaling up Bayesian variational inference using distributed computing clusters. In this paper we present ... approach for scaling up Bayesian learning using variational methods by exploiting distributed computing clusters managed ... models). Our approach compares favorably to stochastic variational inference and streaming variational Bayes...

Salmon
 Referenced in 7 articles
[sw31865]
 read alignments), and massivelyparallel stochastic collapsed variational inference. The result is a versatile tool...

BayesPy
 Referenced in 3 articles
[sw15438]
 removing the tedious task of implementing the variational Bayesian update equations, the user can construct ... Simple syntax, flexible model construction and efficient inference make BayesPy suitable for both average ... some advanced methods such as stochastic and collapsed variational inference...

crowdGPPL
 Referenced in 1 article
[sw34403]
 Individual biases also make it harder to infer the consensus of a crowd when there ... pairwise labels, we propose a stochastic variational inference approach that limits computational and memory costs...

vir
 Referenced in 1 article
[sw37284]
 variational inference with shrinkage priors. Our package implements variational and stochastic variational algorithms for linear ... many applied analyses. We review variational inference and show how the derivation for a Gibbs ... derive a corresponding variational or stochastic variational algorithm. We provide simulations showing that, at least ... normal linear model, variational inference can lead to similar uncertainty quantification as the corresponding Gibbs...

Venture
 Referenced in 10 articles
[sw14670]
 stochastic regeneration and the SPI to implement generalpurpose inference strategies such as MetropolisHastings ... Markov chain Monte Carlo and meanfield variational inference techniques...

Blaise
 Referenced in 8 articles
[sw29867]
 recently focused on the implementation of stochastic search processes such as Markov chain Monte Carlo ... processors and computing clusters, and inference schemes based on variational methods and message passing...

HIBITS
 Referenced in 4 articles
[sw30626]
 model for binary time series with a stochastic component represented by a Gaussian process ... response. The Gaussian process captures the residual variations in the binary response that ... frequentist modeling framework that provides efficient inference and more accurate predictions. Results demonstrate the advantages...

bippdevi
 Referenced in 1 article
[sw42055]
 Variational Bayes (VB) has been recognised as a more computationally tractable method for Bayesian inference ... element discretisation. We utilise stochastic optimisation to efficiently estimate the variational objective and assess...

EvoVGM
 Referenced in 1 article
[sw42445]
 phylogenetic inference framework. In this study, we propose a method for a deep variational Bayesian ... train the model via a lowvariance stochastic estimator and a gradient ascent algorithm. Here...

ADOLC
 Referenced in 257 articles
[sw00019]
 ADOLC: Automatic Differentiation of C/C++. We present...

ANSYS
 Referenced in 713 articles
[sw00044]
 ANSYS offers a comprehensive software suite that spans...

CGAL
 Referenced in 402 articles
[sw00118]
 The goal of the CGAL Open Source Project...

Coq
 Referenced in 1906 articles
[sw00161]
 Coq is a formal proof management system. It...

Expokit
 Referenced in 200 articles
[sw00258]
 Expokit provides a set of routines aimed at...

GAUSS
 Referenced in 120 articles
[sw00322]
 The GAUSS Mathematical and Statistical System is a...

GEANT4
 Referenced in 45 articles
[sw00328]
 Differential elastic hadronnucleus crosssections are discussed...

Gmsh
 Referenced in 783 articles
[sw00366]
 Gmsh is a 3D finite element grid generator...

hypre
 Referenced in 334 articles
[sw00426]
 hypre is a software library for the solution...

LAPACK
 Referenced in 1713 articles
[sw00503]
 LAPACK is written in Fortran 90 and provides...