Search Results for "markov"
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Showing 22 open source projects for "markov"
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We design our technology to make workforce management easier. APS offers core HR, payroll, benefits administration, attendance, recruiting, employee onboarding, and more.
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Define and Deliver Comprehensive Cybersecurity Services. Security threats continue to grow, and your clients are most likely at risk. Small- to medium-sized businesses (SMBs) are targeted by 64% of all cyberattacks, and 62% of them admit lacking in-house expertise to deal with security issues. Now technology solution providers (TSPs) are a prime target. Enter ConnectWise Cybersecurity Management (formerly ConnectWise Fortify) — the advanced cybersecurity solution you need to deliver the managed detection and response protection your clients require. Whether you’re talking to prospects or clients, we provide you with the right insights and data to support your cybersecurity conversation. From client-facing reports to technical guidance, we reduce the noise by guiding you through what’s really needed to demonstrate the value of enhanced strategy.
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
... of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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DifferentialEquations.jl
Multi-language suite for high-performance solvers of equations
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized... -
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OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE)
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research that routinely outperform the “standard” C/Fortran methods, and include algorithms optimized... -
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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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Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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Bridge.jl
A statistical toolbox for diffusion processes
Statistics and stochastic calculus for Markov processes in continuous time, include univariate and multivariate stochastic processes such as stochastic differential equations or diffusions (SDE's) or Levy processes. -
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Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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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. -
Venn is a secure workspace for remote work that isolates and protects work from any personal use on the same computer. Work lives in a secure local enclave that is company controlled, where all data is encrypted and access is managed. Within the enclave – visually indicated by the Blue Border around these applications – business activity is walled off from anything that happens on the personal side. As a result, work and personal uses can now safely coexist on the same computer.
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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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fvm2
FVM2 - F Virtual Machine v2
FVM2 is VM for running machines like Markov algorithms, Turing machine and so on. FVM2 has debugger with step mode and breakpoints. Goal of this project is to help students with studying Theory of computation. FVM2 shows how complex code works within a real machine. Currently the only implemented machine is Markov algorithms. -
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segment
Solve the Viterbi algorithm in a data stream
It is often necessary to assign a series of discrete values to continuosly variable data sequenced by time, position, etc., thereby parsing the data into fewer and larger segments of variable width. The 'segment' utility takes an input data stream as a Hidden Markov Model and applies the Viterbi algorithm to find the most likely segmentation path through the data. -
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CvHMM
Discrete Hidden Markov Models based on OpenCV
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects. -
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HMMLab
A Hidden Markov Model editor with support to HTK
HMMLab is a Hidden Markov Model editor oriented on HMMs for speach recognition. It can create, edit, train and visualize HMMs. HMMLab supports loading/saving HMMs from/to HTK files. -
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T3S Tool
Learning Stochastic Discrete Event Systems
Stochastic discrete event system analysis and verification are essential in order to ensure reliability in such systems. However, models that cannot be constructed with an hand-made process need to be learned. Thus, the SDES toolbox proposes an automated solution that is embedded in Matlab to learning and analisis generalized semi-Markov processes. -
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SpecMark (spectral Markov) is a method for calculating the joint probability distribution over species in a regulatory network.
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Pocket CRF is a modified version of CRF++, it maintains the simplicity of CRF++ and is able to use high order features. Pocket M3N is a simple Max Margin Markov Networks package for sequence labeling tasks.
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depmix is a package for the R statistical computing environment, to fit (multigroup) mixtures of latent Markov models on mixed categorical and continuous (timeseries) data
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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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HmmSDK is a hidden Markov model (HMM) software development kit written in Java. It consists of core library of HMM functions (Forward-backward, Viterbi, and Baum-Welch algorithms) and toolkits for application development.
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CMATLIB is set of libraries for writing numerical applicatons. It includes support for neural-networks, hidden Markov models, kd-trees, and data smoothing. It may be used from C and Scheme programs.
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Two Markov-Chain-Monte-Carlo-algorithms ("Glauber Dynamics" and "Flip Dynamics") used for randomly sampling k-colorings of a graph.
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