Search Results for "bayesian"
Sort By:
Showing 20 open source projects for "bayesian"
View related business solutions-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
Bayes+Estimate is a Rust and C++ library that implement numerical algorithms for Bayesian estimation. They provide tested and consistent numerical methods and represents the wide variety of Bayesian estimation algorithms and system model.
-
2
JAGS is Just Another Gibbs Sampler. It is a program for the statistical analysis of Bayesian hierarchical models by Markov Chain Monte Carlo.
-
3
MOSGWA
genome wide association studies / Bayesian-type information criteria
MOSGWA is a tool for genome wide association studies (GWAS). It currently implements a search strategy using logistic regression and linear regression. -
4
faif
C++ header only library with AI and bioinformatics algorithms
C++ header only library, small and fast; Naive Bayesian Classifier, Decision Tree Classifier (ID3), DNA/RNA nucleotide second structure predictor, timeseries management, timeseries prediction, generic Evolutionary Algorithm, generic Hill Climbing algorithm and others. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
5
BayesAss
Bayesian Inference of Recent Migration Using Multilocus Genotypes
Inference of recent migration rates between populations using multi-locus marker genotype data. -
6
Bayesian Analysis: Neutron Stars, M & R
Bayesian Analysis of Neutron Star Mass and Radius Observations
A Bayesian analysis of neutron star mass and radius observations based on O2scl. -
7
BiomeNet
BAYESIAN INFERENCE OF METABOLIC DIVERGENCE AMONG MICROBIAL COMMUNITIES
...Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. ... -
8
FamSeq
Variant calling on the basis of pedigree information
...FamSeq accommodates de novo mutations and can perform variant calling at chromosome X. 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. -
9
phcfM
R package for modelling anthropogenic deforestation
...It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data 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. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
10
fesslix
Stochastic Analysis
A brief summary of the main features of Fesslix: - Perform non-intrusive reliability analysis or Bayesian updating either --- by running commands on the command line or --- by means of an Octave interface or --- by means of a Python interface - Flexible input language for writing Fesslix parameter files --- Control flow statements (e.g. if, for, while) --- Most parameters can be defined as functions - Working with response surfaces - Linear finite element analysis using truss, beam and plane stress/strain elements - Spectral Stochastic Finite Elements - Bayesian networks This is the download page for Windows executables of Fesslix. -
11
Bayesloc
Bayesian Hierarchical Seismic Event Locator
Given a set of seismic arrivals for one or more events, Bayesloc estimates the joint probability of event locations, corrections to travel time predictions, precision of arrival time measurements, and phase labels for the arrival times. Bayesloc also accepts probabilistic prior constraints on any of the input parameters, which can significantly tighten the distribution of all parameters. -
12
BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
-
13
-
14
-
15
QHQ++ is a C++ library includes: QHQc++ (C++ Numerical Library), QHQmcmc++ (Markov Chain Monte Carlo C++ Library, Bayesian Statistics), QHQsv++ (Stochastic Volatility C++ Library, Finance), QHQyc++ (Yield Curve Modeling C++ Library, Finance).
-
16
A C++ library for Bayesian computation, including a collection of more generally-applicable utilities.
-
17
The Pattern Analysis Library (PALib) is a C++ class library for pattern classification/recognition. PALib consists of a wide range of machine learning routines such as Bayesian decision theory, artificial neural networks, and fuzzy inference systems.
-
18
A general purpose C++ library for Bayesian Filtering.<p> Essentially Bayesian Filtering is a way of having a program learn to categorize information from a specific user through pattern recognition. <p>
-
19
-
20
Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
- Previous
- You're on page 1
- Next
