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Top Pkgs Packages

1

ForwardDiff

Forward Mode Automatic Differentiation for Julia

2

OhMyREPL

Syntax highlighting and other enhancements for the Julia REPL

3

StaticArrays

Statically sized arrays for Julia

4

DiffEqBase

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

5

AdvancedHMC

Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms

6

OffsetArrays

Fortran-like arrays with arbitrary, zero or negative starting indices.

7

SIMD

Explicit SIMD vector operations for Julia

8

DiffEqSensitivity

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.

9

LineSearches

Line search methods for optimization and root-finding

10

ArrayInterface

Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations

11

CpuId

Ask the CPU for cache sizes, SIMD feature support, a running hypervisor, and more.

12

AccurateArithmetic

Calculate with error-free, faithful, and compensated transforms and extended signficands.

13

TransformVariables

Transformations to contrained variables from ℝⁿ.

14

ExponentialUtilities

Utility functions for exponential integrators for the SciML scientific machine learning ecosystem

16

PositiveFactorizations

Positive-definite "approximations" to matrices

17

AxisAlgorithms

Efficient filtering and linear algebra routines for multidimensional arrays