Search Results for "markov"
Sort By:
Showing 17 open source projects for "markov"
View related business solutions-
Our Free Plans just got better! | Auth0 by OktaYou asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your secuirty. Auth0 now, thank yourself later.
-
Deliver secure remote access with OpenVPN.OpenVPN's products provide scalable, secure remote access — giving complete freedom to your employees to work outside the office while securely accessing SaaS, the internet, and company resources.
-
1
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. -
2
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... -
3
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... -
4
JAGS is Just Another Gibbs Sampler. It is a program for the statistical analysis of Bayesian hierarchical models by Markov Chain Monte Carlo.
-
Red Hat Enterprise Linux on Microsoft AzureRed Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
-
5
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
-
6
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. -
7
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.
-
8
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
-
9
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. -
Free CRM Software With Something for EveryoneThink CRM software is just about contact management? Think again. HubSpot CRM has free tools for everyone on your team, and it’s 100% free. Here’s how our free CRM solution makes your job easier.
-
10
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. -
11
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. -
12
SpecMark (spectral Markov) is a method for calculating the joint probability distribution over species in a regulatory network.
-
13
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.
-
14
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
-
15
Algorithms to estimate the number of k-colorings of a low-degree graph using samplings from a markov chain are provided.
-
16
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.
-
17
Two Markov-Chain-Monte-Carlo-algorithms ("Glauber Dynamics" and "Flip Dynamics") used for randomly sampling k-colorings of a graph.
- Previous
- You're on page 1
- Next