Search Results for "markov chain"
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Showing 27 open source projects for "markov chain"
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
...TFP is open source and available on GitHub. Tools to build deep probabilistic models, including probabilistic layers and a `JointDistribution` abstraction. Variational inference and Markov chain Monte Carlo. A wide selection of probability distributions and bijectors. Optimizers such as Nelder-Mead, BFGS, and SGLD. -
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Meridian
Meridian is an MMM framework
...The framework provides a robust foundation for constructing in-house MMM pipelines capable of handling both national and geo-level data, with built-in support for calibration using experimental data or prior knowledge. Meridian uses the No-U-Turn Sampler (NUTS) for Markov Chain Monte Carlo (MCMC) sampling to produce statistically rigorous results, and it includes GPU acceleration to significantly reduce computation time. -
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Bayesian Statistics
This repository holds slides and code for a full Bayesian statistics
This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used... -
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Gen.jl
A general-purpose probabilistic programming system
...Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. But it also lets users migrate parts of their model or inference algorithm to specialized modeling languages for which it can generate especially fast code. ... -
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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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Anti-Spam SMTP Proxy Server
Anti-Spam SMTP Proxy Server implements multiple spam filters
The Anti-Spam SMTP Proxy (ASSP) Server project aims to create an open source platform-independent SMTP Proxy server which implements auto-whitelists, self learning Hidden-Markov-Model and/or Bayesian, Greylisting, DNSBL, DNSWL, URIBL, SPF, SRS, Backscatter, Virus scanning, attachment blocking, Senderbase and multiple other filter methods. Click 'Files' to download the professional version 2.8.1 build 24261. A linux(ubuntu 20.04 LTS) and a freeBSD 12.2 based ready to run OVA of ASSP V2 are... -
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Java Modelling Tools is a suite of scientific tools for performance analysis and modelling using queueing theory and colored stochastic Petri nets. Models are solved either with analytical, asymptotic or simulation methods; workload characterization tools are also included in the suite. See the project website for more details: http://jmt.sf.net
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XD1DD
XD1DD: X-ray Diffraction for 1 Dimensional Disorder
The computer program is designed to calculate powder X-ray diffraction patterns for one-dimensionally (1D) disordered crystals, i.e. containing planar defects. Calculations are made on the basis of statistical models, where the Markov chain with stationary transition probabilities is used as a probabilistic rule for generating a 1D disordered sequence of layers. The model takes into account the short-range order in the alternation and methods of layer superposition, which allows simulating various cases of distribution of planar defects in crystals. To obtain a powder diffraction pattern, calculations are carried out in three-dimensional reciprocal space along rods passing through the nodes of the reciprocal two-dimensional lattice. ... -
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MonteCarlo.jl
Classical and quantum Monte Carlo simulations in Julia
MonteCarlo.jl is a package implementing classical and quantum Monte Carlo simulations primarily for solid state physics. Currently the focus is on finding a overall design for the package and verifying that determinant Quantum Monte Carlo (DQMC) is working correctly. As such the package may still go through significant changes and the documentation may be outdated and incomplete. Note that classical Monte Carlo is also not a focus at this point. It is probably usable, but a lot of the... -
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node-markov-generator
Generates simple sentences based on given text corpus
This simple generator emits short sentences based on the given text corpus using a Markov chain. To put it simply, it works kinda like word suggestions that you have while typing messages in your smartphone. It analyzes which word is followed by which in the given corpus and how often. And then, for any given word it tries to predict what the next one might be. Here you create an instance of TextGenerator passing an array of strings to it - it represents your text corpus which will be used to "train" the generator. ... -
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IMMpractical implements various Markov chain model-based methods for analysis of DNA sequences. Please cite: Sparks, M.E., Brendel, V. and Dorman, K.S. (2007) Markov model variants for appraisal of coding potential in plant DNA. LNBI. 4463:394-405.
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Carnatic Music Guru / JRaaga
Carnatic Music Guru - JRaaga
VISIT THIS PAGE AS MORE FEATURES ARE BEING ADDED. If you have downloaded 2.03 or above - Use Help>Check Updates to download latest version. If that does not update: Download CMGUpdater from here: update/CMGUpdater.jar Copy it to the update/ folder of your JRaaga installation path. Try again Help>Check for updates. If it does not work. Delete existing installation. Download the latest version and try. Carnatic Music Guru is a tutor/player/lesson generator. YOU NEED Java Runtime... -
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Spotlight
Deep recommender models using PyTorch
...Spotlight offers a slew of popular datasets, including Movielens 100K, 1M, 10M, and 20M. It also incorporates utilities for creating synthetic datasets. For example, generate_sequential generates a Markov-chain-derived interaction dataset, where the next item a user chooses is a function of their previous interactions. Recommendations can be seen as a sequence prediction task: given the items a user has interacted with in the past, what will be the next item they will interact with? Spotlight provides a range of models. -
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Muninn
A software package for estimating generalized ensemble weights in Mark
We have moved to GitHub: https://github.com/muninnorg/muninn As of July 2015 we have moved to GitHub. The SourceForge page will preserved, with the old releases. Muninn is a software package for estimating generalized ensemble weights in Markov chain Monte Carlo (MCMC) simulations. The method is full automated and makes use of the generalized multihistogram (GMH) equations for estimation the density of states [1]. The package is implemented in C++ and has a convenient interface. -
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StatAlign
An extendable statistical multiple alignment tool.
StatAlign is an extendable software package for Bayesian analysis of Protein, DNA and RNA sequences. Multiple alignments, phylogenetic trees and evolutionary parameters are co-estimated in a Markov Chain Monte Carlo framework, allowing for reliable measurement of the accuracy of the results. This approach eliminates common artifacts that traditional methods suffer from, at the cost of increased computational time. These artifacts include the dependency of the constructed phylogeny on a single (probably suboptimal) alignment and bias towards the guide tree upon which the alignment relies. ... -
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FamSeq
Variant calling on the basis of pedigree information
...To accommodate variations in data complexity, FamSeq consists of three distinct implementations of the Mendelian genetic model: the Bayesian network algorithm, Elston-Stewart algorithm and Markov chain Monte Carlo algorithm. To make the software efficient and applicable to large families, we parallelized the Bayesian network algorithm that copes with pedigrees with inbreeding loops without losing calculation precision on an NVIDIA® graphics processing unit. -
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Hrothgar Parallel LM/MCMC Minimizer
A versatile MCMC and downhill optimization engine
Hrothgar is a parallel minimizer and Markov Chain Monte Carlo generator by Andisheh Mahdavi of San Francisco State University. It has been used to solve optimization problems in astrophysics (galaxy cluster mass profiles) as well as in experimental particle physics (hadronic tau decays). It is probably adaptable enough to be applied to your merit function if you can write it in C. -
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FAUST2
Formal Abstractions of Uncountable-STate STochastic processes
FAUST2 is a software tool that generates formal abstractions of (possibly non-deterministic) discrete-time Markov processes (dtMP) defined over uncountable (continuous) state spaces. A dtMP model is specified in MATLAB and abstracted as a finite-state Markov chain or Markov decision processes. The abstraction procedure runs in MATLAB and employs parallel computations and fast manipulations based on vector calculus. The abstract model is formally put in relationship with the concrete dtMP via a user-defined maximum threshold on the approximation error introduced by the abstraction procedure. ... -
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HYDRA is an open-source, platform-neutral library for performing Markov Chain Monte Carlo. It implements the logic of standard MCMC samplers within a framework designed to be easy to use and to extend while allowing integration with other software to
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ESMERALDA is a development environment for statistical recognizers operating on sequential data (speech, handwriting, biological sequences). It supports continuous density Hidden Markov models, Markov chain (N-gramm) models, and Gaussian mixture models.
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Matlab toolbox for Markov Chain Monte Carlo. Includes interfaces for storing and retrieving trace and run information.
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Algorithms to estimate the number of k-colorings of a low-degree graph using samplings from a markov chain are provided.
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NullAllEst is the implementation of a maximum likelihood algorithm to estimate the frequency of a null allele in microsatellite genetic data. A Markov Chain Monte Carlo simulation is used to solve the likelihood function.
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Generates nicknames that sound like real words after analyzing a dictionary, using a so-called Markov chain
