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JuliaDiff

23 indexed repositories · View on GitHub

ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia

Julia · 1005 stars
BlueStyle
A Julia style guide that lives in a blue world

519 stars
ChainRules.jl
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs

Julia · 475 stars
Diffractor.jl
Next-generation AD

Julia · 453 stars
ReverseDiff.jl
Reverse Mode Automatic Differentiation for Julia

Julia · 393 stars
TaylorSeries.jl
Taylor polynomial expansions in one and several independent variables.

Julia · 388 stars
FiniteDifferences.jl
High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)

Julia · 318 stars
DifferentiationInterface.jl
An interface to various automatic differentiation backends in Julia.

Julia · 313 stars
FiniteDiff.jl
Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support

Julia · 304 stars
ChainRulesCore.jl
AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for...

Julia · 267 stars
AbstractDifferentiation.jl
An abstract interface for automatic differentiation.

Julia · 138 stars
TaylorDiff.jl
Taylor-mode automatic differentiation for higher-order derivatives

Julia · 83 stars
DualNumbers.jl
Julia package for representing dual numbers and for performing dual algebra

Julia · 80 stars
DiffRules.jl
A simple shared suite of common derivative definitions

Julia · 74 stars
Capstan.jl
A Cassette-based automatic differentiation package for the Julia language

Julia · 56 stars
ChainRulesTestUtils.jl
Utilities for testing custom AD primitives.

Julia · 50 stars
SparseMatrixColorings.jl
Coloring algorithms for sparse Jacobian and Hessian matrices

Julia · 45 stars
HyperDualNumbers.jl
Julia implementation of HyperDualNumbers

Julia · 43 stars
DiffResults.jl
A package which provides an API for querying differentiation results at multiple orders simultaneously

Julia · 37 stars
PolyesterForwardDiff.jl

Julia · 34 stars
3 more repositories live on View on GitHub

Beginner friendly Everything

Open All

Add a benchmark suite Open

Difficulty 5/5 Over a week Newbie friendliness 35/100

JuliaDiff/TaylorSeries.jl#428 · Opened Sep 14, 2026
DIT errors with custom types in contexts Open

Difficulty 2/5 1-3 hours Newbie friendliness 68/100

JuliaDiff/DifferentiationInterface.jl#1069 · Opened Sep 12, 2026
Residual allocations in in-place nested Taylor1s methods Open

Difficulty 3/5 1-2 days Newbie friendliness 68/100

JuliaDiff/TaylorSeries.jl#424 · 1 comment · Opened Sep 10, 2026
`gradient!` leaves part of the result unwritten when `f` does not depend on its argument Open

Difficulty 3/5 1-2 days Newbie friendliness 78/100

JuliaDiff/ForwardDiff.jl#847 · Opened Sep 1, 2026
hessian!(::ImmutableDiffResult, f, ::StaticArray) errors when f does not depend on its argument Open

Difficulty 3/5 1-2 days Newbie friendliness 76/100

JuliaDiff/ForwardDiff.jl#846 · 1 comment · Opened Sep 1, 2026
hessian: the two nested dual layers share a tag, so results depend on the code path and chunk size Open

Difficulty 4/5 3-5 days Newbie friendliness 64/100

JuliaDiff/ForwardDiff.jl#845 · Opened Sep 1, 2026
AutoEnzyme Jacobian preparation scalar-indexes Reactant traced arrays Open

backend wontfix

Difficulty 4/5 3-5 days Newbie friendliness 52/100

JuliaDiff/DifferentiationInterface.jl#1066 · 10 comments · Opened Aug 26, 2026
Reusing a `GradientConfig`/`JacobianConfig` with a differently structured input silently computes wrong derivatives Open

Difficulty 4/5 3-5 days Newbie friendliness 38/100

JuliaDiff/ForwardDiff.jl#842 · Opened Aug 19, 2026
Chunked `jacobian` throws for `Diagonal`/`LowerTriangular`/`UpperTriangular` inputs Open

Difficulty 4/5 3-5 days Newbie friendliness 38/100

JuliaDiff/ForwardDiff.jl#839 · Opened Aug 17, 2026
`gradient!` writes to the wrong entries for structured inputs Open

Difficulty 3/5 1-2 days Newbie friendliness 74/100

JuliaDiff/ForwardDiff.jl#838 · Opened Aug 17, 2026
Take advantage of symmetry in `hessian` Open

Difficulty 5/5 Over a week Newbie friendliness 35/100

JuliaDiff/ForwardDiff.jl#836 · 3 comments · Opened Aug 15, 2026
Split preparation methods into 4 Open

Difficulty 4/5 3-5 days Newbie friendliness 48/100

JuliaDiff/DifferentiationInterface.jl#1059 · Opened Aug 14, 2026
Add ThreadedHessianConfig for HyperHessians Open

Difficulty 5/5 Over a week Newbie friendliness 35/100

JuliaDiff/DifferentiationInterface.jl#1058 · Opened Aug 14, 2026
AutoEnzyme forward-mode jacobian() silently returns wrong values for closure-captured arrays reused unmodified in vcat Open

backend

Difficulty 4/5 3-5 days Newbie friendliness 52/100

JuliaDiff/DifferentiationInterface.jl#1057 · 1 comment · Opened Aug 14, 2026
Allow passing `y` to `prepare!_same_point` Open

Difficulty 3/5 1-2 days Newbie friendliness 35/100

JuliaDiff/DifferentiationInterface.jl#1055 · Opened Aug 14, 2026
Should `hessian` return a `Symmetric` matrix? Open

Difficulty 5/5 Over a week Newbie friendliness 35/100

JuliaDiff/TaylorSeries.jl#423 · 1 comment · Opened Aug 11, 2026
Feat: A third preparation mode between `strict=Val(true)` and `strict=Val(false)`: fall back to unprepared execution on signature mismatch Open

Difficulty 4/5 3-5 days Newbie friendliness 52/100

JuliaDiff/DifferentiationInterface.jl#1052 · Opened Aug 7, 2026
3-arg `hypot` flattens `Dual`s with different tags, and rejects non-`Type` tags Open

Difficulty 3/5 1-2 days Newbie friendliness 72/100

JuliaDiff/ForwardDiff.jl#834 · Opened Aug 5, 2026
checktag's permissive fallback silently disables tag checking (e.g. for derivative(f!, y, x, cfg)) Open

Difficulty 4/5 3-5 days Newbie friendliness 50/100

JuliaDiff/ForwardDiff.jl#833 · Opened Aug 5, 2026
jacobian(f!, y, x) doesn't work if y is complex Open

Difficulty 3/5 1-2 days Newbie friendliness 35/100

JuliaDiff/ForwardDiff.jl#832 · Opened Aug 5, 2026
jacobian(f, x) silently returns zeros if f is complex-valued Open

Difficulty 3/5 1-2 days Newbie friendliness 75/100

JuliaDiff/ForwardDiff.jl#830 · Opened Aug 5, 2026
derivative(f!, y, x) doesn't work if y is complex, even if x is real Open

Difficulty 3/5 1-2 days Newbie friendliness 52/100

JuliaDiff/ForwardDiff.jl#818 · 1 comment · Opened Jun 25, 2026
Contributors Open

wontfix

Difficulty 5/5 Over a week Newbie friendliness 20/100

JuliaDiff/SparseMatrixColorings.jl#331 · 4 comments · Opened Jun 25, 2026
Compiled (trimmed) binaries Open

Difficulty 5/5 Over a week Newbie friendliness 35/100

JuliaDiff/SparseMatrixColorings.jl#329 · 2 comments · 2 reactions · Opened Jun 25, 2026
TagBot: Manual intervention needed for releases Open

tagbot-manual

Difficulty 2/5 1-3 hours Newbie friendliness 55/100

JuliaDiff/FiniteDiff.jl#218 · Opened Jun 23, 2026
Contributors Open

wontfix

Difficulty 1/5 Under an hour Newbie friendliness 35/100

JuliaDiff/DifferentiationInterface.jl#1028 · 7 comments · Opened Jun 17, 2026
Define `==` for `JetSpace` Open

Difficulty 2/5 1-3 hours Newbie friendliness 68/100

JuliaDiff/TaylorSeries.jl#417 · 11 comments · Opened Jun 15, 2026
tagging API? Open

Difficulty 5/5 Over a week Newbie friendliness 25/100

JuliaDiff/ForwardDiff.jl#813 · Opened Jun 8, 2026
Deferred computation for precompilable tags? Open

Difficulty 5/5 Over a week Newbie friendliness 35/100

JuliaDiff/ForwardDiff.jl#812 · 1 reaction · Opened Jun 7, 2026
Feature request: Coverage in DifferentiationInterfaceTest Open

documentation

Difficulty 5/5 Over a week Newbie friendliness 30/100

JuliaDiff/DifferentiationInterface.jl#1024 · 9 comments · Opened Jun 1, 2026
TagBot: Manual intervention needed for releases Open

tagbot-manual

Difficulty 1/5 Under an hour Newbie friendliness 45/100

JuliaDiff/FiniteDifferences.jl#250 · 1 comment · Opened May 25, 2026
Bug(Enzyme): SecondOrder(ForwardDiff, AutoEnzyme(Reverse)) silently returns 0 from second_derivative Open

bot

Difficulty 4/5 3-5 days Newbie friendliness 45/100

JuliaDiff/DifferentiationInterface.jl#1017 · Opened May 20, 2026
Bug(ChainRules): gradient/pullback return NoTangent instead of zeros when f does not depend on x Open

bot

Difficulty 3/5 1-2 days Newbie friendliness 72/100

JuliaDiff/DifferentiationInterface.jl#1016 · Opened May 20, 2026
Bug(GTPSA): gradient/jacobian/hessian/hvp fail and pushforward returns wrong values when f does not depend on x Open

bot

Difficulty 3/5 1-2 days Newbie friendliness 68/100

JuliaDiff/DifferentiationInterface.jl#1015 · Opened May 20, 2026
Bug(FastDifferentiation): hessian returns wrong values when a variable appears inside a nonlinear op and as a multiplier Open

bot

Difficulty 4/5 3-5 days Newbie friendliness 55/100

JuliaDiff/DifferentiationInterface.jl#1014 · 3 comments · Opened May 20, 2026
Bug(FiniteDiff): hvp accuracy under AutoFiniteDiff() defaults disagrees with hessian Open

bot

Difficulty 4/5 3-5 days Newbie friendliness 52/100

JuliaDiff/DifferentiationInterface.jl#1012 · 3 comments · Opened May 20, 2026
Bug(Zygote): derivative fails when Zygote returns nothing gradient Open

bot

Difficulty 2/5 1-3 hours Newbie friendliness 68/100

JuliaDiff/DifferentiationInterface.jl#1011 · 3 comments · Opened May 20, 2026
Bug(Mooncake): jacobian for real→complex functions returns Float64 instead of ComplexF64 Open

bot

Difficulty 4/5 3-5 days Newbie friendliness 35/100

JuliaDiff/DifferentiationInterface.jl#1010 · Opened May 18, 2026
Bug(ForwardDiff): jacobian/derivative returns Dual numbers for real→complex functions Open

bot

Difficulty 4/5 3-5 days Newbie friendliness 45/100

JuliaDiff/DifferentiationInterface.jl#1009 · 1 comment · Opened May 18, 2026
Info: DI is running an agentic bug finding experiment Open

bot wontfix

Difficulty 5/5 Over a week Newbie friendliness 10/100

JuliaDiff/DifferentiationInterface.jl#1008 · 2 reactions · Opened May 18, 2026
Test two different points for derivative computations Open

test

Difficulty 3/5 1-2 days Newbie friendliness 52/100

JuliaDiff/DifferentiationInterface.jl#1007 · Opened May 18, 2026
The proper way to do automatic sparse differentiation on GPU Open

documentation gpu

Difficulty 3/5 1-2 days Newbie friendliness 48/100

JuliaDiff/DifferentiationInterface.jl#997 · 10 comments · Opened Apr 25, 2026
Option for Native AD backend APIs to offer direct stability guarantees ? Open

backend core

Difficulty 5/5 Over a week Newbie friendliness 25/100

JuliaDiff/DifferentiationInterface.jl#993 · 18 comments · Opened Apr 17, 2026
PR proposal: `AutoBatch`-batch/vectorized AD backend Open

core

JuliaDiff/DifferentiationInterface.jl#991 · 10 comments · 1 assignee · Opened Apr 12, 2026
SpecialFunctions.jl could be a weak dep? Open

Difficulty 4/5 3-5 days Newbie friendliness 35/100

JuliaDiff/ForwardDiff.jl#800 · 1 comment · Opened Apr 5, 2026
Feature request: vectorized finite difference evaluation Open

Difficulty 5/5 Over a week Newbie friendliness 45/100

JuliaDiff/FiniteDiff.jl#210 · 1 comment · 1 reaction · Opened Mar 31, 2026
documentation: clarify role of mutable arguments for operators like `jacobian!` Open

core documentation

Difficulty 3/5 1-2 days Newbie friendliness 45/100

JuliaDiff/DifferentiationInterface.jl#977 · 4 comments · Opened Mar 7, 2026
GPU array preservation and parallelism in wrong mode Open

core gpu

Difficulty 5/5 Over a week Newbie friendliness 35/100

JuliaDiff/DifferentiationInterface.jl#971 · Opened Feb 23, 2026
GPU scalar indexing when `transpose(::CuArray)` Open

gpu

Difficulty 4/5 3-5 days Newbie friendliness 35/100

JuliaDiff/DifferentiationInterface.jl#970 · 12 comments · Opened Feb 23, 2026
Failing MiniZinc tests Open

Difficulty 4/5 3-5 days Newbie friendliness 25/100

JuliaDiff/SparseMatrixColorings.jl#303 · Opened Feb 18, 2026

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