autodifferentiation
There are 49 repositories under autodifferentiation topic.
coreylowman/dfdx
Deep learning in Rust, with shape checked tensors and neural networks
autodiff/autodiff
automatic differentiation made easier for C++
neuronika/neuronika
Tensors and dynamic neural networks in pure Rust.
lmfit/uncertainties
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
rsokl/MyGrad
Drop-in autodiff for NumPy.
JamesYang007/FastAD
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
rejuvyesh/PyCallChainRules.jl
Differentiate python calls from Julia
tiandiweizun/autodiff
200行写一个自动微分工具
yizhang-yiz/fazang
Fazang is a Fortran library for reverse-mode automatic differentiation, inspired by Stan/Math library.
abap34/JITrench.jl
[wip] Lightweight Automatic Differentiation & DeepLearning Framework implemented in pure Julia.
Renovamen/flint
A toy deep learning framework implemented in pure Numpy from scratch. Aka homemade PyTorch lol.
3outeille/Yaae
Yaae: Yet another autodiff engine (written in Numpy).
bpesquet/pyfit
A minimalist neural networks library built on a tiny autograd engine
Nicholaswogan/ForwardDiff
Forward mode automatic differentiation for Fortran
oberbichler/HyperJet
Algorithmic differentiation with hyper-dual numbers in C++ and Python
scala-infer/scala-infer
Scala embedded universal probabilistic programming language
codereckons/fluxion
C++20 numerical and analytical derivative computations
RSuryaNarayan/CEMA
Chemical Explosive Mode Analysis for computational/experimental combustion diagnostics using Julia SciML features
sreenivasanramesh/MachineLearningSystems
Assignments for Data Intensive Systems for Machine Learning Coursework
gbelouze/forward-gradient
Experiments with forward gradients on optimization test functions
rillki/tiny-autodiff
A tiny autograd library made for educational purposes.
Eshaancoding/AutoDiff
Automatic differentiation: A tool that allows you to calculate multivariable equations, vectors, matrices, and more. All done in C++, no libraries!
briochemc/F1Method.jl
F-1 method
isaacveg/Yacc-lex-for-reversed-automatic-differentiation
yacc lex for reversed automatic differentiation
metabolize-forks/chumpy
Fork of Matt Loper's autodifferentiation framework for Python
oberbichler/HyperGraph
Reversed mode second order automatic differentiation for python (WIP)
ahmadyan/Jet
Autodifferentiation engine forked from Ceres-Solver
theolepage/tensorflood
Tiny automatic differentiation (autodiff) engine for NumPy tensors implemented in Python.
Howuhh/autograd_but_smaller
Simple implementation of reverse-mode automatic differentiation on numpy arrays
ai-glimpse/toydl
toydl: toy deep learning algorithms implementation, backend with self implement toy torch
EnzymeAD/enzyme-dev-docker
🚢 Portable development environment for Enzyme
gden173/nanograd
A Micrograd inspired (and largely copied) small autodiff engine.
jaimeliew1/Dualitic
Dualitic is a Python package for forward mode automatic differentiation using dual numbers.
marcromani/cascade
Lightweight automatic differentiation and error propagation library
michaellavelle-archive/autograd
A tiny autograd adapter implemented in Java with PyTorch-like API.
rixsilverith/nablagrad
Yet another automatic differentiation engine to perform efficient and analytically precise partial differentiation of mathematical expressions.