All Packages
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Relationals.jl1Simple, fast access to relational data sources. Inspired by Rails ActiveRecord.
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Pack1.jl1A single-file Julia libray using pack(1) alignment to pack value-typed instances into UInt8 arrays with extensible endianness.
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ProjectAssistant.jl1Assistant to create new julia projects
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StatsProcedures.jl1An interface framework for sharing intermediate steps across statistical methods
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Simplex.jl1Practice project: a program that performs the simplex algorithm.
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ParametricDFNOs.jl1-
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OutlierDetectionTrees.jl1-
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SparseArraysCOO.jl1Create sparse vectors and matrices conveniently and efficiently
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QuantumESPRESSOParser.jl1Parses the input/output files of Quantum ESPRESSO to extract data
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ModifiedLatinHypercubeSampling.jl1Efficient simulation techniques
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ParametricLP.jl1-
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Thorn.jl1-
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ModiaResult.jl1Abstract interface and base functions for simulation results
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PPInterpolation.jl1Piecewise polynomial interpolation in Julia
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Osnaps.jl1Optical Spectroscopy Numerical Analysis and Processing Tools
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Proportions.jl1-
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Orthopolys.jl1Orthogonal polynomials
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OrthoMatchingPursuit.jl1-
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Paraml.jl1Param yaml
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ThreadLocalCounters.jl1-
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SpmImageTycoonInstaller.jl1Installer for SpmImage Tycoon
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OptiTrack.jl1Receive NatNet messages from OptiTrack motion capture system
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Scats.jl1Spectral correlation analysis of time series (not supposed to be used)
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ProductArrays.jl1A lazy array acting like `collect(Iterators.product(it...))`
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SQLCompose.jl1Relational composition
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OptionType.jl1Rust like Option Types (Some and None)
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Optionals.jl1Julia Optionals Package
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SIGPROCFiles.jl1I/O for SIGPROC filterbank and time series files, in Julia.
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ModuleLogging.jl1Global logging for your own modules only!
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PhysicalMeshes.jl1Physical mesh interfaces for Julia
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Scalar.jl1Scalar Types
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OptimizationTestFunctions.jl1-
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OptimizationAlgorithms.jl1-
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ToolipsDefaults.jl1Default servables for toolips
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StackedHourglass.jl1-
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StackedNets.jl1-
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PartedArrays.jl1-
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PartialSvdStoch.jl1Partial Svd with Random Sampling. O.Shamir and Vempala algorithms.
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ProximalMethods.jl1Provides proximal operator evaluation routines and proximal optimization algorithms, such as (accelerated) proximal gradient methods and alternating direction method of multipliers (ADMM), for non-smooth/non-differentiable objective functions.
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StagedFilters.jl1-