Showing 26 open source projects for "probability"

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    Intelligent predictive dialer for outbound call center

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  • 1
    MathPHP

    MathPHP

    Powerful modern math library for PHP

    Math PHP is a library that brings advanced mathematical functions and data analysis capabilities to PHP applications. It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing.
    Downloads: 5 This Week
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  • 2
    ProbabilisticCircuits.jl

    ProbabilisticCircuits.jl

    Probabilistic Circuits from the Juice library

    ...Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units). Given certain structural properties, PCs enable different range of tractable exact probabilistic queries such as computing marginals, conditionals, maximum a posteriori (MAP), and more advanced probabilistic queries.
    Downloads: 3 This Week
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  • 3
    Pyro

    Pyro

    Deep universal probabilistic programming with Python and PyTorch

    ...It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable abstractions that make it both agile and maintainable. Lastly, Pyro gives you the flexibility of automation when you want it, and control when you need it.
    Downloads: 3 This Week
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  • 4
    Hasktorch

    Hasktorch

    Tensors and neural networks in Haskell

    Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions....
    Downloads: 3 This Week
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    Shoplogix Smart Factory Platform

    For manufacturers looking for a powerful Manufacturing Execution solution

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  • 5
    RuoYi

    RuoYi

    The warehouse's SpringBoot-based rights management system

    ...She can be used for all web applications, such as website management background, website member center, CMS, CRM, OA. All front-end and back-end codes are very compact and easy to use after encapsulation, and the probability of errors is low. Also supports mobile client access. The system will continue to update some useful functions. The user is the system operator, and this function mainly completes the system user configuration. Configure the system organization (company, department, group).
    Downloads: 4 This Week
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  • 6
    Gonum

    Gonum

    Set of numeric libraries for the Go programming language

    ...Gonum is a set of packages designed to make writing numerical and scientific algorithms productive, performant, and scalable. Gonum contains libraries for matrices and linear algebra; statistics, probability distributions, and sampling; tools for function differentiation, integration, and optimization; network creation and analysis; and more. We encourage you to get started with Go and Gonum if you are tired of sluggish performance, and fighting C and vectorization, and also if you are struggling with managing programs as they grow larger. ...
    Downloads: 4 This Week
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  • 7
    ramsey/uuid

    ramsey/uuid

    A PHP library for generating universally unique identifiers (UUIDs)

    ...A universally unique identifier, or UUID, is a 128-bit unsigned integer, usually represented as a hexadecimal string split into five groups with dashes. The most widely-known and used types of UUIDs are defined by RFC 4122. The probability of duplicating a UUID is close to zero, so they are a great choice for generating unique identifiers in distributed systems. UUIDs can also be stored in binary format, as a string of 16 bytes. The JSON extension is normally enabled by default, but it is possible to disable it. Other required extensions include PCRE and SPL. These standard extensions cannot be disabled without patching PHP’s build system and/or C sources.
    Downloads: 6 This Week
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  • 8
    PyMC3

    PyMC3

    Probabilistic programming in Python

    ...Sometimes an unknown parameter or variable in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets.
    Downloads: 2 This Week
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  • 9
    latexify

    latexify

    A library to generate LaTeX expression from Python code

    ...It parses Python functions and expressions into an abstract syntax tree (AST), applies symbolic rewrites for common mathematical constructs, and then emits LaTeX that compiles cleanly in standard environments. Typical use cases include turning analytical utilities—like probability mass functions, activation formulas, or recurrence relations—into equations suitable for papers, notebooks, and slide decks. The tool aims to preserve semantics such as exponentiation, summations, products, piecewise definitions, and function application while hiding Pythonic scaffolding. Users can control rendering details for names and operators so the output conforms to a project’s notation style. ...
    Downloads: 1 This Week
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  • The most advanced C and C++ source code analyzer Icon
    The most advanced C and C++ source code analyzer

    Combining the benefits of static and dynamic source code analysis to deliver the most advanced & exhaustive code verification tool.

    TrustInSoft Analyzer is a C and C++ source code analyzer powered by formal methods, mathematical & logical reasonings that allow for exhaustive analysis of source code. This analysis can be run without false positives or false negatives, so that every real bug in the code is found. Developers receive several benefits: a user-friendly graphical interface that directs developers to the root cause of bugs, and instant utility to expand the coverage of their existing tests. Unlike traditional source code analysis tools, TrustInSoft’s solution is not only the most comprehensive approach on the market but is also progressive, instantly deployable by developers, even if they lack experience with formal methods, from exhaustive analysis up to a functional proof that the software developed meets specifications.
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  • 10
    LibRan

    LibRan

    Random Variate generators for various distributions.

    The LibRan package is a library of various pseudo-random number generators along with their exact probability and cumulative probability density functions. The libary contains its own optimized sequential congruential uniform pseudo-random number generator on the interval x ∈ [0, 1) ; along with useful tools such as methods for collecting statistics in bins. Each of the random variate distributions rely on a number of internal attributes to customize the distribution. ...
    Downloads: 0 This Week
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  • 11
    Statistical Rethinking 2022

    Statistical Rethinking 2022

    Statistical Rethinking course winter 2022

    ...The code emphasizes Bayesian data analysis using R, the rethinking package, and Stan models. It includes lecture code files, example datasets, and structured exercises that parallel the topics covered in the lectures (probability, regression, model comparison, Bayesian updating). The repo functions as a direct hands-on reference for students following the 2022 recorded lecture series. There are 10 weeks of instruction. Links to lecture recordings will appear in this table. Weekly problem sets are assigned on Fridays and due the next Friday, when we discuss the solutions in the weekly online meeting.
    Downloads: 2 This Week
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  • 12
    Big List of Naughty Strings

    Big List of Naughty Strings

    List of strings which have a high probability of causing issues

    The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer...
    Downloads: 0 This Week
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  • 13
    Kalman and Bayesian Filters in Python

    Kalman and Bayesian Filters in Python

    Kalman Filter book using Jupyter Notebook

    ...All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. What better way to learn? This book teaches you how to solve all sorts of filtering problems. Use many different algorithms, all based on Bayesian probability. In simple terms Bayesian probability determines what is likely to be true based on past information. This book is interactive. While you can read it online as static content, it's better to use it as intended. It is written using Jupyter Notebook, which allows you to combine text, math, Python, and Python output in one place.
    Downloads: 0 This Week
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  • 14
    DeepLearning

    DeepLearning

    Deep Learning (Flower Book) mathematical derivation

    ...The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. ...
    Downloads: 3 This Week
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  • 15
    PRMLT

    PRMLT

    Matlab code of machine learning algorithms in book PRML

    ...Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry.
    Downloads: 0 This Week
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  • 16
    Probability Cheatsheet

    Probability Cheatsheet

    A comprehensive 10-page probability cheatsheet

    The probability_cheatsheet is a cheat sheet repository that summarizes key probability theory concepts, formulas, distributions, and properties in a concise format. It likely includes definitions of random variables, PMFs and PDFs, expectations, variance, common distributions (e.g. binomial, normal, Poisson, exponential), conditional probability, Bayes’ theorem, moment generating functions, and perhaps important inequalities (Markov, Chebyshev, Chernoff).
    Downloads: 0 This Week
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  • 17
    wxpy

    wxpy

    Probably the most elegant Wechat personal number API

    On the basis of itchat, wxpy improves the ease of use of the module through a large number of interface optimizations and provides rich function expansion. All in all, it can be used to automate the operation of various WeChat personal accounts. Judging from the recent feedback (late June 2017), there is a certain probability that the use of robots may be restricted from logging in. It is mainly manifested in the inability to log in to Web WeChat (but does not affect other platforms such as mobile phones). Comprehensive object-oriented interface, more elegant invocation. Default multi-threaded response message, faster reply. Contains practical. Receive warnings with WeChat in other projects with just two lines of code. ...
    Downloads: 0 This Week
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  • 18
    Solar Wi-Fi weather station on ESP12

    Solar Wi-Fi weather station on ESP12

    Solar Wi-Fi weather station on ESP12

    #ESP.Meteo: Solar Wi-Fi weather station on ESP12 + ionistor + solar panel Current Functionality: *Forecasting the probability of frosts (according to the methods of Professor Brounov) *Forecast of the height of the lower edge of the cloud (VNGO by Selezneva) *Calculation of the height of the sensor according to the barometric formula (altimeter, for other projects) *Measurement of street temperature *Measurement of outdoor humidity *Measurement of street pressure *Calculation of the dew point *Monitoring of voltage on ionistors (charge-discharge control) *Monitoring the opening of the box flap with potatoes *Monitoring the system time-out every 5 minutes (operating time ~ 480 ms) *Monitoring the temperature on the balcony (the ability to connect up to 16 sensors DS18B20: 2 groups of 8 sensors per two APIKEY) *Sending data to the Thingspeak cloud *Sending data to Twitter
    Downloads: 5 This Week
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  • 19
    Investing

    Investing

    Investing Returns on the Market as a Whole

    ...The key insight illustrated is that over sufficiently long holding periods (e.g. 40 years), the stock market stabilizes and nearly always yields positive returns, even accounting for extreme market crashes and recessions. The visualizations show “return curves” for different starting years and durations, and also illustrate the probability of losses over various time horizons. The project is centered on transparency in finance and encourages users to examine the data themselves; the code is shared in R and uses ggplot2 for plotting.
    Downloads: 0 This Week
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  • 20
    RStan

    RStan

    RStan, the R interface to Stan

    RStan is the R interface to Stan, a C++ library for statistical modeling and high-performance statistical computation. It lets users specify models in the Stan modeling language (for Bayesian inference), compile them, and perform inference from R. Key inference approaches include full Bayesian inference via Hamiltonian Monte Carlo (specifically the No-U-Turn Sampler, NUTS), approximate Bayesian inference via variational methods, and optimization (penalized likelihood). RStan integrates with...
    Downloads: 2 This Week
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  • 21
    Ava: Testdata Xsl

    Ava: Testdata Xsl

    generates Testdata on base of excel: creates xml,excel,csv,html,sql,+

    this tool for test-data-generation receives an 'excel-sheet' as primary input. second important paramter is the 'number of test-records to produce'. The excel-data will be reused as long data is needed. This tool is hightly paramatrisazable by the use of 'xsl scripts'. data can be created, updated, modified and finally exported in a format of your choice Main Fuctions: (1) Generates Testdata (excel, xsl, xml) (2) Exports generated testdata in multiple formats (csv, excel, html,...
    Downloads: 0 This Week
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  • 22
    QPNet

    QPNet

    Synchronous Petri Nets' emulator

    QPNet (Quick Petri Net) is a fast Petri Nets' emulator, created by students of Moscow State Technical University of Radio Engineering, Electronics and Automation. It brings benefits for the educational process, while being under further development and extension. QPNet это быстрый эмулятор сетей Петри, созданный студентами МИРЭА. Он применяется в учебном процессе, а так же продолжает разрабатываться и эволюционировать.
    Downloads: 0 This Week
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  • 23
    K-Surfer

    K-Surfer

    A KNIME extension for the management and analysis of FreeSurfer Data

    ...K-Surfer consists of a suite of KNIME nodes that perform several tasks, such as importing diffusion data generated from TRACULA, importing morphological measures obtained from the segmentation and reconstruction of neuroimages and visualising the probability distribution of white matter pathways. For installation guide read the pdf inside the zip. References: Sarica Alessia, Giuseppe Di Fatta, and Mario Cannataro. "K-Surfer: A KNIME Extension for the Management and Analysis of Human Brain MRI FreeSurfer/FSL Data." Brain Informatics and Health. Springer International Publishing, 2014. 481-492. ...
    Downloads: 0 This Week
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  • 24
    A small command line tool to process streams of numbers and spit out the running total, bin the results or merge duplicates. Supports arbitrary precision numbers. ocdf is named for the cumulative distribution function in probability.
    Downloads: 0 This Week
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  • 25

    EZvolve Foundation Classes

    Data types and utility classes for use with evolutionary algorithms.

    EZvolve Foundation Classes is a set of data types and utility classes for use with evolutionary algorithms. Currently implemented support for bit string encoding, populations, fitnesses, fitness functions, probabilities, and probability vectors.
    Downloads: 0 This Week
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