Dependency Packages
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Turing.jl1807Bayesian inference with probabilistic programming.
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MLJ.jl1589A Julia machine learning framework
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DiffEqTutorials.jl694Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
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GeoStats.jl414An extensible framework for high-performance geostatistics in Julia
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StatisticalRethinking.jl366Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.
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MCMCChains.jl236Types and utility functions for summarizing Markov chain Monte Carlo simulations
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Stan.jl197Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.
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ReservoirComputing.jl172Reservoir computing utilities for scientific machine learning (SciML)
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TuringModels.jl153Implementations of the models from the Statistical Rethinking book with Turing.jl
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EvoTrees.jl143Boosted trees in Julia
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MLJBase.jl140Core functionality for the MLJ machine learning framework
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DiffEqBayes.jl117Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
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MLJFlux.jl115Wrapping deep learning models from the package Flux.jl for use in the MLJ.jl toolbox
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ClimateTools.jl108Climate science package for Julia
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LightGBM.jl81Julia FFI interface to Microsoft's LightGBM package
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CounterfactualExplanations.jl75A package for Counterfactual Explanations and Algorithmic Recourse in Julia.
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EasyModelAnalysis.jl74High level functions for analyzing the output of simulations
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MLJLinearModels.jl74Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)
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BetaML.jl72Beta Machine Learning Toolkit
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OutlierDetection.jl69Fast, scalable and flexible Outlier Detection with Julia
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MLJModels.jl67Home of the MLJ model registry and tools for model queries and mode code loading
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Turkie.jl65Turing + Makie = Turkie
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Econometrics.jl61Econometrics in Julia
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MLJTuning.jl60Hyperparameter optimization algorithms for use in the MLJ machine learning framework
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TuringGLM.jl58Bayesian Generalized Linear models using `@formula` syntax.
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ConformalPrediction.jl58Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.
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CalibrateEmulateSample.jl50Stochastic Optimization, Learning, Uncertainty and Sampling
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ParallelKMeans.jl49Parallel & lightning fast implementation of available classic and contemporary variants of the KMeans clustering algorithm
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Ripserer.jl45Flexible and efficient persistent homology computation.
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Dynare.jl44A Julia rewrite of Dynare: solving, simulating and estimating DSGE models.
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GeoArrays.jl44Simple geographical raster interaction built on top of ArchGDAL, GDAL and CoordinateTransformations
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ImageQuilting.jl37Fast image quilting simulation solver for the GeoStats.jl framework
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MCMCBenchmarks.jl37Comparing performance and results of mcmc options using Julia
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PartialLeastSquaresRegressor.jl34Implementation of a Partial Least Squares Regressor
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NestedSamplers.jl33Implementations of single and multi-ellipsoid nested sampling
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Fairness.jl29Julia Toolkit with fairness metrics and bias mitigation algorithms
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TreeParzen.jl28TreeParzen.jl, a pure Julia hyperparameter optimiser with MLJ integration
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NearestNeighborModels.jl27Package providing K-nearest neighbor regressors and classifiers, for use with the MLJ machine learning framework.
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ODINN.jl27Global glacier model using Universal Differential Equations for climate-glacier interactions
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MCMCTempering.jl27Implementations of parallel tempering algorithms to augment samplers with tempering capabilities
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