Showing 14 open source projects for "bayesian python"

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  • 1
    PyMC

    PyMC

    Bayesian Modeling and Probabilistic Programming in Python

    PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling.
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  • 2
    BATS

    BATS

    Bayesian Adaptive Trial Simulator

    A user-friendly, quick simulator for Bayesian Multi-Arm Multi-Stage Trials
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  • 3
    BayesRate

    BayesRate

    Bayesian estimation of diversification rates

    BayesRate is a program to estimate speciation and extinction rates from dated phylogenies in a Bayesian framework. The methods are described in: Silvestro, D., Schnitzler, J. and Zizka, G. (2011) A Bayesian framework to estimate diversification rates and their variation through time and space. BMC Evolutionary Biology, 11, 311 Silvestro D., Zizka G. & Schulte K. (2014) Disentangling the effects of key innovations on the diversification of Bromelioideae (Bromeliaceae). Evolution, 68, 163-175.
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  • 4

    Pyclamp

    A Python package used to extract and analyse electrophysiological data

    ...Quantal analysis : This part of the package performs simple variance-mean analysis and Bayesian quantal analysis to estimate the quantal sizea dn number of release sites among other measures.
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  • 5

    PyRate

    Bayesian Estimation of Speciation and Extinction from Fossil Data

    PyRate is a Python program to estimate speciation, extinction, and preservation rates from fossil occurrence data using a Bayesian framework. The method was described by D Silvestro, J Schnitzler, LH Liow, A Antonelli, and N Salamin in Systematic Biology (http://sysbio.oxfordjournals.org/content/early/2014/02/08/sysbio.syu006.abstract). *Please download the most up-to-date code from the "PyRate code" tab on this page or from: https://github.com/dsilvestro/PyRate * *An updated manual can be found here: https://github.com/dsilvestro/PyRate/tree/master/tutorials *
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  • 6
    fesslix

    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.
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  • 7
    Provide a reference implementation of Moving Taylor Bayesian Regression, a method for nonparametric multi-dimensional function estimation with correlated errors from finite samples, as a Python package based on SciPy
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  • 8
    Open Bayes is a python free/open library that allows users to easily create a bayesian network and perform inference/learning on it. It is mainly inspired from the Bayes Net Toolbox (BNT) but uses python as a base language. www.openbayes.org
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  • 9
    Feedisto is your personal newspaper. Your newspaper is collocted from rss feeds, parsed by a bayesian filter to rate its relevance and served as a static html page or on a webserver to train the filter. Writing plugins is very easy.
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    Accounts Payable Software | AvidXchange

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  • 10
    A python/C++ framework for Bayesian phylogenetic analysis.
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  • 11
    BASILISK
    BASILISK is a probabilistic model of the conformational space of amino acid side chains in proteins. Unlike rotamer libraries, BASILISK models the chi angles in continuous space, including the influence of the protein's backbone.
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  • 12
    DANGLE: A Bayesian inferential prediction method for protein backbone dihedral angles and secondary structure assignments, solely from sequence information, experimental chemical shifts and a database of known protein structures and their shifts.
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  • 13
    This is a Python package for general Bayesian inference.
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  • 14
    RISO: distributed, heterogeneous Bayesian belief networks. Belief network: a probability model defined on an acyclic directed graph; distributed: nodes can be on different hosts; and heterogeneous: allowing different types of conditional distributions.
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