Showing 38 open source projects for "model-builder"

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  • 1
    Mixed-effects models in Julia

    Mixed-effects models in Julia

    A Julia package for fitting (statistical) mixed-effects models

    This package defines linear mixed models (LinearMixedModel) and generalized linear mixed models (GeneralizedLinearMixedModel). Users can use the abstraction for statistical model API to build, fit (fit/fit!), and query the fitted models. A mixed-effects model is a statistical model for a response variable as a function of one or more covariates. For a categorical covariate the coefficients associated with the levels of the covariate are sometimes called effects, as in "the effect of using...
    Downloads: 1 This Week
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  • 2
    ACME.jl

    ACME.jl

    Analog Circuit Modeling and Emulation for Julia

    ACME is a Julia package for the simulation of electrical circuits, focusing on audio effect circuits. It allows one to programmatically describe a circuit in terms of elements and connections between them and then automatically derive a model for the circuit. The model can then be run on varying input data.
    Downloads: 1 This Week
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  • 3
    CliMA Land

    CliMA Land

    Everything within the Land model

    CliMA Land is a next generation Land Surface Model (LSM) designed to use the broadly available remote sensing data as well as ground-based flux measurements. CliMA Land is a highly modular platform to promote research at different scales from tissue to organ, whole plant, and ecosystem. Therefore, we deliver CliMA Land via a patch of packages (also referred to as sub-modules) to reduce the time used to initialize a research project. As a result, the repository is more a collection of tutorials...
    Downloads: 1 This Week
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  • 4
    LIBSVM.jl

    LIBSVM.jl

    LIBSVM bindings for Julia

    LIBSVM bindings for Julia. This is a Julia interface for LIBSVM and for the linear SVM model provided by LIBLINEAR. Supports all LIBSVM models: classification C-SVC, nu-SVC, regression: epsilon-SVR, nu-SVR and distribution estimation: one-class SVM. Model objects are represented by Julia-type SVM which gives you easy access to model features and can be saved e.g. as JLD file.
    Downloads: 0 This Week
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  • 5
    Yggdrasil

    Yggdrasil

    Collection of builder repositories for BinaryBuilder.jl

    This repository contains recipes for building binaries for Julia packages using BinaryBuilder.jl.
    Downloads: 0 This Week
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  • 6
    ModelingToolkitStandardLibrary.jl

    ModelingToolkitStandardLibrary.jl

    A standard library of components to model the world and beyond

    The ModelingToolkit Standard Library is a standard library of components to model the world and beyond.
    Downloads: 0 This Week
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  • 7
    BinaryBuilder

    BinaryBuilder

    Binary Dependency Builder for Julia

    Binary Dependency Builder for Julia. Building binary packages is a pain. BinaryBuilder follows a philosophy that is similar to that of building Julia itself; when you want something done right, you do it yourself. To that end, BinaryBuilder is designed from the ground up to facilitate the building of packages within an easily reproducible and reliable Linux environment, ensuring that the built libraries and executables are deployable to every platform that Julia itself will run on. Packages...
    Downloads: 0 This Week
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  • 8
    Wflow.jl

    Wflow.jl

    Hydrological modeling

    ... model concepts are available, which maximizes the use of open earth observation data, making it the hydrological model of choice for data-scarce environments. Based on gridded topography, soil, land use and climate data, wflow calculates all hydrological fluxes at any given grid cell in the model at a given time step.
    Downloads: 0 This Week
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  • 9
    Surrogates.jl

    Surrogates.jl

    Surrogate modeling and optimization for scientific machine learning

    A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. The idea is then to develop a surrogate model g which approximates f by training on previous data collected from evaluations...
    Downloads: 0 This Week
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  • 10
    Bayesian Statistics

    Bayesian Statistics

    This repository holds slides and code for a full Bayesian statistics

    This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used...
    Downloads: 0 This Week
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  • 11
    ArviZ.jl

    ArviZ.jl

    Exploratory analysis of Bayesian models with Julia

    ArviZ.jl (pronounced "AR-vees") is a Julia package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, model checking, comparison and diagnostics.
    Downloads: 0 This Week
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  • 12
    ExplainableAI.jl

    ExplainableAI.jl

    Explainable AI in Julia

    This package implements interpretability methods for black box models, with a focus on local explanations and attribution maps in input space. It is similar to Captum and Zennit for PyTorch and iNNvestigate for Keras models. Most of the implemented methods only require the model to be differentiable with Zygote. Layerwise Relevance Propagation (LRP) is implemented for use with Flux.jl models.
    Downloads: 0 This Week
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  • 13
    UMAP.jl

    UMAP.jl

    Uniform Manifold Approximation and Projection (UMAP) implementation

    A pure Julia implementation of the Uniform Manifold Approximation and Projection dimension reduction algorithm. The umap function takes two arguments, X (a column-major matrix of shape (n_features, n_samples)), n_components (the number of dimensions in the output embedding), and various keyword arguments.
    Downloads: 0 This Week
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  • 14
    JuliaConnectoR

    JuliaConnectoR

    A functionally oriented interface for calling Julia from R

    This R-package provides a functionally oriented interface between R and Julia. The goal is to call functions from Julia packages directly as R functions. Julia functions imported via the JuliaConnectoR can accept and return R variables. It is also possible to pass R functions as arguments in place of Julia functions, which allows callbacks from Julia to R. From a technical perspective, R data structures are serialized with an optimized custom streaming format, sent to a (local) Julia TCP...
    Downloads: 0 This Week
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  • 15
    MLJBase.jl

    MLJBase.jl

    Core functionality for the MLJ machine learning framework

    Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ.
    Downloads: 0 This Week
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  • 16
    PowerSystems.jl

    PowerSystems.jl

    Data structures in Julia to enable power systems analysis

    The PowerSystems.jl package provides a rigorous data model using Julia structures to enable power systems analysis and modeling. In addition to stand-alone system analysis tools and data model building, the PowerSystems.jl package is used as the foundational data container for the PowerSimulations.jl and PowerSimulationsDynamics.jl packages. PowerSystems.jl supports a limited number of data file formats for parsing.
    Downloads: 0 This Week
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  • 17
    PowerSimulationsDynamics.jl

    PowerSimulationsDynamics.jl

    Julia package to run Dynamic Power System simulations

    PowerSimulationsDynamics.jl is a Julia package for power system modeling and simulation of Power Systems dynamics.
    Downloads: 0 This Week
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  • 18
    oneAPI.jl

    oneAPI.jl

    Julia support for the oneAPI programming toolkit.

    Julia support for the oneAPI programming toolkit. oneAPI.jl provides support for working with the oneAPI unified programming model. The package is verified to work with the (currently) only implementation of this interface that is part of the Intel Compute Runtime, only available on Linux. This package is still under significant development, so expect bugs and missing features.
    Downloads: 0 This Week
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  • 19
    Parameters.jl

    Parameters.jl

    Types w/ default field values, keyword constructors, (un-)pack macros

    This is a package I use to handle numerical-model parameters, thus the name. However, it should be useful otherwise too.
    Downloads: 0 This Week
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  • 20
    ReactiveMP.jl

    ReactiveMP.jl

    High-performance reactive message-passing based Bayesian engine

    ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets.
    Downloads: 0 This Week
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  • 21
    The ARCHModels Package for Julia

    The ARCHModels Package for Julia

    A Julia package for estimating ARMA-GARCH models

    ARCH (Autoregressive Conditional Heteroskedasticity) models are a class of models designed to capture a feature of financial returns data known as volatility clustering, i.e., the fact that large (in absolute value) returns tend to cluster together, such as during periods of financial turmoil, which then alternate with relatively calmer periods. This package provides efficient routines for simulating, estimating, and testing a variety of GARCH models. ARCH (Autoregressive Conditional...
    Downloads: 0 This Week
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  • 22
    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...
    Downloads: 0 This Week
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  • 23
    DiffOpt.jl

    DiffOpt.jl

    Differentiating convex optimization programs w.r.t. program parameters

    ... theory, control theory and machine learning. Recent work has shown how to differentiate specific subclasses of convex optimization problems. But several applications remain unexplored. With the help of automatic differentiation, differentiable optimization can have a significant impact on creating end-to-end differentiable systems to model neural networks, stochastic processes, or a game.
    Downloads: 0 This Week
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  • 24
    ConformalPrediction.jl

    ConformalPrediction.jl

    Predictive Uncertainty Quantification through Conformal Prediction

    ConformalPrediction.jl is a package for Predictive Uncertainty Quantification (UQ) through Conformal Prediction (CP) in Julia. It is designed to work with supervised models trained in MLJ (Blaom et al. 2020). Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use...
    Downloads: 0 This Week
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  • 25
    Circuitscape.jl

    Circuitscape.jl

    Algorithms from circuit theory to predict connectivity

    Circuitscape is an open-source program that uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. Julia is built from the ground up to be fast. As such, this offers a number of advantages over...
    Downloads: 0 This Week
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