Showing 4 open source projects for "fixed"

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  • Red Hat Enterprise Linux on Microsoft Azure Icon
    Red Hat Enterprise Linux on Microsoft Azure

    Deploy Red Hat Enterprise Linux on Microsoft Azure for a secure, reliable, and scalable cloud environment, fully integrated with Microsoft services.

    Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
  • Business Continuity Solutions | ConnectWise BCDR Icon
    Business Continuity Solutions | ConnectWise BCDR

    Build a foundation for data security and disaster recovery to fit your clients’ needs no matter the budget.

    Whether natural disaster, cyberattack, or plain-old human error, data can disappear in the blink of an eye. ConnectWise BCDR (formerly Recover) delivers reliable and secure backup and disaster recovery backed by powerful automation and a 24/7 NOC to get your clients back to work in minutes, not days.
  • 1
    Mixed-effects models in Julia

    Mixed-effects models in Julia

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

    ... Treatment 1 versus the placebo". If the potential levels of the covariate are fixed and reproducible, e.g. the levels for Sex could be "F" and "M", they are modeled with fixed-effects parameters. If the levels constitute a sample from a population, e.g. the Subject or the Item at a particular observation, they are modeled as random effects.
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  • 2
    ImplicitDifferentiation.jl

    ImplicitDifferentiation.jl

    Automatic differentiation of implicit functions

    ImplicitDifferentiation.jl is a package for automatic differentiation of functions defined implicitly, i.e., forward mappings. Those for which automatic differentiation fails. Reasons can vary depending on your backend, but the most common include calls to external solvers, mutating operations or type restrictions. Those for which automatic differentiation is very slow. A common example is iterative procedures like fixed point equations or optimization algorithms.
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  • 3
    HCubature.jl

    HCubature.jl

    Pure-Julia multidimensional h-adaptive integration

    ... space). You can integrate real, complex, and matrix-valued integrands, for example. Note that HCubature assumes that your function f(x) can be computed at arbitrary points in the integration domain. (This is the ideal way to do numerical integration.) If you instead have f(x) precomputed at a fixed set of points, such as a Cartesian grid, you will need to use some other method (e.g. Trapz.jl for a multidimensional trapezoidal rule).
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  • 4
    SimpleTraits.jl

    SimpleTraits.jl

    Simple Traits for Julia

    This package provides a macro-based implementation of traits, using Tim Holy's trait trick. The main idea behind traits is to group types outside the type-hierarchy and to make dispatch work with that grouping. The difference to Union-types is that types can be added to a trait after the creation of the trait, whereas Union types are fixed after creation. The cool thing about Tim's trick is that there is no performance impact compared to using ordinary dispatch. For a bit of background...
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  • Control remote support software for remote workers and IT teams Icon
    Control remote support software for remote workers and IT teams

    Raise the bar for remote support and reduce customer downtime.

    ConnectWise ScreenConnect, formerly ConnectWise Control, is a remote support solution for Managed Service Providers (MSP), Value Added Resellers (VAR), internal IT teams, and managed security providers. Fast, reliable, secure, and simple to use, ConnectWise ScreenConnect helps businesses solve their customers' issues faster from any location. The platform features remote support, remote access, remote meeting, customization, and integrations with leading business tools.
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