Search Results for "java open source" - Page 8

Showing 460 open source projects for "java open source"

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  • 1
    SciML Style Guide for Julia

    SciML Style Guide for Julia

    A style guide for stylish Julia developers

    The SciML Style Guide is a style guide for the Julia programming language. It is used by the SciML Open Source Scientific Machine Learning Organization. As such, it is open to discussion with the community. If the standard for code contributions is that every PR needs to support every possible input type that anyone can think of, the barrier would be too high for newcomers. Instead, the principle is to be as correct as possible to begin with, and grow the generic support over time. ...
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  • 2
    VoronoiFVM.jl

    VoronoiFVM.jl

    Solution of nonlinear multiphysics partial differential equations

    Solver for coupled nonlinear partial differential equations (elliptic-parabolic conservation laws) based on the Voronoi finite volume method. It uses automatic differentiation via ForwardDiff.jl and DiffResults.jl to evaluate user functions along with their jacobians and calculate derivatives of solutions with respect to their parameters.
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  • 3
    CausalInference.jl

    CausalInference.jl

    Causal inference, graphical models and structure learning in Julia

    Julia package for causal inference and analysis, graphical models and structure learning. This package contains code for the PC algorithm and the extended FCI algorithm, the score based greedy equivalence search (GES) algorithm, the Bayesian Causal Zig-Zag sampler and a function suite for adjustment set search.
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  • 4
    Winston.jl

    Winston.jl

    2D plotting for Julia

    2D plotting for Julia. Winston offers an easy-to-use plot command to create figures without any fuss. After Winston is loaded by typing using Winston, the most basic plot can be created.
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    Lightspeed golf course management software

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  • 5
    Hecke.jl

    Hecke.jl

    Computational algebraic number theory

    Hecke is a software package for algebraic number theory maintained by Claus Fieker, Tommy Hofmann and Carlo Sircana. It is written in julia and is based on the computer algebra packages Nemo and AbstractAlgebra. Hecke is part of the OSCAR project and the development is supported by the Deutsche Forschungsgemeinschaft DFG within the Collaborative Research Center TRR 195.
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  • 6
    Calculus.jl

    Calculus.jl

    Calculus functions in Julia

    The Calculus package provides tools for working with the basic calculus operations of differentiation and integration. You can use the Calculus package to produce approximate derivatives by several forms of finite differencing or to produce exact derivatives using symbolic differentiation. You can also compute definite integrals by different numerical methods.
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  • 7
    MAT.jl

    MAT.jl

    Julia module for reading MATLAB files

    Julia module for reading MATLAB files. Read and write MATLAB files in Julia. This library can read MATLAB .mat files, both in the older v4/v5/v6/v7 format, as well as the newer v7.3 format.
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  • 8
    Krylov.jl

    Krylov.jl

    A Julia Basket of Hand-Picked Krylov Methods

    If you use Krylov.jl in your work, please cite it using the metadata given in CITATION.cff.
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  • 9
    FastGaussQuadrature.jl

    FastGaussQuadrature.jl

    Julia package for Gaussian quadrature

    A Julia package to compute n-point Gauss quadrature nodes and weights to 16-digit accuracy and in O(n) time. So far the package includes gausschebyshev(), gausslegendre(), gaussjacobi(), gaussradau(), gausslobatto(), gausslaguerre(), and gausshermite(). This package is heavily influenced by Chebfun.
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  • 10
    Oxygen.jl

    Oxygen.jl

    A breath of fresh air for programming web apps in Julia

    A breath of fresh air for programming web apps in Julia. Oxygen is a micro-framework built on top of the HTTP.jl library. Breathe easy knowing you can quickly spin up a web server with abstractions you're already familiar with.
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  • 11
    DataDrivenDiffEq.jl

    DataDrivenDiffEq.jl

    Data driven modeling and automated discovery of dynamical systems

    DataDrivenDiffEq.jl is a package for finding systems of equations automatically from a dataset. The methods in this package take in data and return the model which generated the data. A known model is not required as input. These methods can estimate equation-free and equation-based models for discrete, continuous differential equations or direct mappings.
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  • 12
    Dash Bootstrap Components

    Dash Bootstrap Components

    Bootstrap components for Plotly Dash

    dash-bootstrap-components is a library of Bootstrap components for use with Plotly Dash, that makes it easier to build consistently styled Dash apps with complex, responsive layouts.
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  • 13
    Tokenize.jl

    Tokenize.jl

    Tokenization for Julia source code

    Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens.
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  • 14
    Transformers.jl

    Transformers.jl

    Julia Implementation of Transformer models

    Transformers.jl is a Julia library that implements Transformer models for natural language processing tasks. Inspired by architectures like BERT, GPT, and T5, the library offers a modular and flexible interface for building, training, and using transformer-based deep learning models. It supports training from scratch and fine-tuning pretrained models, and integrates with Flux.jl for automatic differentiation and optimization.
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  • 15
    Tidier.jl

    Tidier.jl

    Meta-package for data analysis in Julia, modeled after the R tidyverse

    Tidier.jl is a Julia package that brings tidyverse-style data manipulation and analysis to Julia, inspired by R's dplyr and tidyverse. It allows users to write expressive and concise data transformation code using chaining (|>) and intuitive syntax. Built on top of DataFrames.jl, Tidier.jl aims to make data wrangling more accessible to users familiar with R or looking for cleaner data pipelines in Julia.
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  • 16
    HTTP.jl

    HTTP.jl

    HTTP for Julia

    HTTP.jl is a pure Julia implementation of the HTTP protocol, providing tools for building HTTP clients and servers. It enables users to send requests, handle responses, and construct REST APIs or web services entirely in Julia. HTTP.jl supports TLS, cookies, headers, streaming, and middleware, making it suitable for both simple scripting and full-scale web service development.
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  • 17
    Dagger.jl

    Dagger.jl

    A framework for out-of-core and parallel execution

    Dagger.jl is a framework for out-of-core and parallel computing in Julia that allows users to construct and execute dynamic task graphs. It is designed for large-scale, distributed, and memory-efficient computations. Dagger supports lazy evaluation and scheduling across multiple threads or machines, enabling high-performance workflows for data processing, scientific computing, and machine learning.
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  • 18
    PkgTemplates.jl

    PkgTemplates.jl

    Create new Julia packages, the easy way

    PkgTemplates.jl is a Julia package that automates the creation of new Julia packages by generating a project scaffold with common best practices. It helps users quickly set up reproducible project structures with Git integration, CI configuration, testing frameworks, documentation, and more. By using customizable templates, PkgTemplates streamlines package development and enforces consistency across Julia projects.
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  • 19
    DSGE.jl

    DSGE.jl

    Solve and estimate Dynamic Stochastic General Equilibrium models

    DSGE.jl is a Julia package developed by the Federal Reserve Bank of New York for estimating and analyzing dynamic stochastic general equilibrium (DSGE) models. It provides tools for Bayesian estimation, filtering, forecasting, and model comparison, supporting both academic research and policy applications. DSGE.jl includes pre-configured models used by central banks and offers extensibility for custom macroeconomic modeling.
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  • 20
    Bumper.jl

    Bumper.jl

    Bring Your Own Stack

    Bumper.jl is a package that aims to make working with bump allocators (also known as arena allocators) easier and safer. You can dynamically allocate memory to these bump allocators, and reset them at the end of a code block, just like Julia's stack. Allocating to a bump allocator with Bumper.jl can be just as efficient as stack allocation. Bumper.jl is still a young package, and may have bugs. Let me know if you find any.
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  • 21
    101-0250-00

    101-0250-00

    ETH course - Solving PDEs in parallel on GPUs

    This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering.
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  • 22
    InferOpt.jl

    InferOpt.jl

    Combinatorial optimization layers for machine learning pipelines

    InferOpt.jl is a toolbox for using combinatorial optimization algorithms within machine learning pipelines. It allows you to create differentiable layers from optimization oracles that do not have meaningful derivatives. Typical examples include mixed integer linear programs or graph algorithms.
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  • 23
    LineSearches.jl

    LineSearches.jl

    Line search methods for optimization and root-finding

    Line search methods for optimization and root-finding. This package provides an interface to line search algorithms implemented in Julia. The code was originally written as part of Optim, but has now been separated out to its own package.
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  • 24
    MultilayerGraphs.jl

    MultilayerGraphs.jl

    Julia package for the creation and analysis of multilayer graphs

    MultilayerGraphs.jl is a Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs. A multilayer graph is a graph consisting of multiple standard subgraphs called layers which can be interconnected through bipartite graphs called interlayers composed of the vertex sets of two different layers and the edges between them. The vertices in each layer represent a single set of nodes, although not all nodes have to be represented in...
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  • 25
    NetCDF.jl

    NetCDF.jl

    NetCDF support for the julia programming language

    NetCDF support for the Julia programming language, there is a high-level and a medium-level interface for writing and reading netcdf files. The dimensions "x1" and "t" of the variable are called "x1" and "t" in this example. If the dimensions do not exist yet in the file, they will be created. The dimension "x1" will be of length 10 and have the values 11..20, and the dimension "t" will have length 20 and the attribute "units" with the value "s".
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