Julia bindings for the Enzyme automatic differentiator

Update immutable data

CliMA model dycore

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Calculating contour curves for 2D scalar fields in Julia

A package containing a library of moist thermodynamic relations.

LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.

Simple, consistent interfaces for any codec.

The Base interface of the SciML ecosystem

Powerful convenience for Julia visualizations and data analysis

Primitives for construction of objects

A package for Gaussian random field generation in Julia

MPI wrappers for Julia

HDF5-compatible file format in pure Julia

AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.

Forward Mode Automatic Differentiation for Julia

SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia

Convert julia objects to LaTeX equations, arrays or other environments.

Julia implementation of Data structures

An interface to various automatic differentiation backends in Julia.

A structure interface for SciML to give queryable properties from user data and parameters

Tools for generating cubed sphere grids and solving partial differential equations on the sphere.

Julia macro for re-exporting one module from another

Julia bindings to the FFTW library for fast Fourier transforms

Julia wrapper for the LLVM C API

A library of cloud microphysics parameterizations

Formatted output of timed sections in Julia

Julia functional programming infrastructures and metaprogramming facilities

Direct solution of large sparse systems of linear algebraic equations in pure Julia

Mathematical functions related to statistics.

Heterogeneous programming in Julia

Abstract julia interfaces for working with trees

Optimization functions for Julia

Basic statistics for Julia

A data structure for mathematical optimization problems

A common solve function for scientific machine learning (SciML) and beyond

Repository for automatic differentiation backend types

A Julia package to provide C and Python-like formatting support

The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

BlockArrays for Julia