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Showing 12 open source projects for "gibbs"
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JAGS is Just Another Gibbs Sampler. It is a program for the statistical analysis of Bayesian hierarchical models by Markov Chain Monte Carlo.
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy. -
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LSA runs based on C++ for Gibbs samplers and R / Rcpp for data preprocessing and posterior sample analysis. The Tempest depends on the Stan math library. We should build the Stan math library, and then you can build the executable.
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runjags
The 'runjags' R package and standalone JAGS extension module
This package provides high-level interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax... -
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jLDADMM
A Java package for the LDA and DMM topic models
The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/ -
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Mocapy++ is a Dynamic Bayesian Network toolkit, implemented in C++. It supports discrete, multinomial, Gaussian, Kent, Von Mises and Poisson nodes. Inference and learning is done by Gibbs sampling/Stochastic-EM.
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phcfM
R package for modelling anthropogenic deforestation
... and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time. -
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RedLDA
Redundancy Aware LDA Gibbs Sampler
Redundancy-Aware Topic Modeling Copy Paste Redundancy or Data Duplication are prevalent in many corpora.This redundancy has a negative impact on the quality of text mining and topic modeling in particular. This is a software package of a novel variant of Latent Dirichlet Allocation (LDA) topic modeling, Red-LDA, which takes into account the inherent redundancy of corpora when modeling content. My site: http://www.cs.bgu.ac.il/~cohenrap/ Lab site:... -
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After about a year's design and coding, now a advanced version of Solucalc has been developed. The advanced version is called ISLEC, which used a Particle swarm based Gibbs free energy minimization approach to solve the equilibrium problem. At the same time, the Pitzer's model proposed by C. E. Harvie & J. Weare in 1980 was persisted. ISLEC has many features: 1. Single point calculation was used instead of line calculation 2. Database was used instead of putting all the parameters...
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A Java Implementation of Latent Dirichlet Allocation (LDA) using Gibbs Sampling for Parameter Estimation and Inference
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GibbsLDA++: A C/C++ Implementation of Latent Dirichlet Allocation (LDA) using Gibbs Sampling for parameter estimation and inference. GibbsLDA++ is fast and is designed to analyze hidden/latent topic structures of large-scale (text) data collections.
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