auto-differentiation

There are 1 repository under auto-differentiation topic.

NVIDIA / MinkowskiEngine
Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors
3d-convolutional-network 3d-vision 4d-convolutional-neural-network auto-differentiation computer-vision convolutional-neural-networks cuda deep-learning high-dimensional-data high-dimensional-inference minkowski-engine neural-network pytorch semantic-segmentation space-time sparse-convolution sparse-tensor-network sparse-tensors spatio-temporal-analysis trilateral-filter
Language:Python 2292
autodiff / autodiff
automatic differentiation made easier for C++
automatic-differentiation auto-differentiation autodiff autodifferentiation differentiation derivatives numerical-derivation
Language:C++ 1528
c0dearm / mushin
Computational graphs with reverse automatic differentation in the GPU
auto-differentiation deep-learning machine-learning rust
Language:Rust 384
anassinator / ilqr
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
trajectory-optimization differential-dynamic-programming theano dynamics-models auto-differentiation model-predictive-control model-predictive-controller control-systems cartpole pendulum ilqr non-linear-optimization trajectory-tracking ilqg mpc mpc-control ddp optimal-control
Language:Python 340
abess-team / skscope
skscope: Sparse-Constrained OPtimization via itErative-solvers
auto-differentiation jax non-convex-optimization nonlinear-optimization python scikit-learn sparsity-optimization
Language:Python 275
EnzymeAD / oxide-enzyme
Enzyme integration into Rust. Experimental, do not use.
ad auto-differentiation derivative enzyme gradient rust
Language:Rust 101
JamesYang007 / FastAD
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
auto-differentiation autodiff autodifferentiation automatic-differentiation cpp17 derivatives differentiation linux macos math
Language:C++ 92
thtrieu / essence
AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.
machine-learning dropout lstm mnist lenet neural-turing-machines question-answering computational-graphs auto-differentiation convolutional-neural-networks convolutional-networks recurrent-neural-networks lstm-model deep-learning deep-q-network reinforcement-learning cartpole
Language:Python 74
DENG-MIT / Arrhenius.jl
Differentiable Reacting Flow Modeling Software
combustion sciml julialang machine-learning deeplearning auto-differentiation cantera reaction flame energy neuralode cvode sundials arrhenius chemistry neural-network cfd
Language:Jupyter Notebook 51
AkiRusProd / numpy-nn-model
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
auto-diff auto-differentiation autodiff autoencoder autograd automatic-differentiation convolutional-neural-network deep-learning gan generative-adversarial-network machine-learning mnist neural-network numpy-model numpy-neural-network vae variational-autoencoder
Language:Python 40
metamath1 / noviceml
도서 머신러닝·딥러닝에 필요한 기초 수학 with 파이썬의 예제 코드와 그래프 그리는 코드 및 웹앱 저장소
mechine-learing deep-learning linear-regression derivatives auto-differentiation optimization functions
Language:Jupyter Notebook 36
supremacyfuture / VQC
variational quantum circuit simulator in Julia, under GPLv3
quantum-circuit auto-differentiation quantum-gates quantum-state variational-quantum-circuit
Language:Julia 32
anassinator / gp
Differentiable Gaussian Process implementation for PyTorch
pytorch gaussian-processes gaussian-process-regression artificial-intelligence machine-learning auto-differentiation
Language:Python 21
TensorBFS / dTRG
tensor-network auto-differentiation pytorch-implementation
Language:Python 16
HyperJet
oberbichler / HyperJet
Algorithmic differentiation with hyper-dual numbers in C++ and Python
automatic-differentiation auto-differentiation autodiff autodifferentiation differentiation derivatives numerical-derivation gradient hessian dual-numbers algorithmic-differentiation hyper-dual-numbers
Language:C++ 13
zoziha / auto-diff
Fortran backward (reverse) mode automatic differentiation.
auto-differentiation backward fpm modern-fortran sigmoid diff automatic-differentiation
Language:Fortran 11
sharan-dce / autograd
Auto-differentiation library for C++
vector graph computation-graphs gradient autograd auto-differentiation
Language:C++ 10
JaimeRZP / LimberJack.jl
Auto-differentiable methods for Cosmology
auto-differentiation cosmology
Language:Julia 9
slimgroup / JutulDarcyRules.jl
JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy
auto-differentiation fluid-flow julia numerical-solver scalable two-phase-flow
Language:Julia 9
termoshtt / cagra
Tiny calculation graph library
calculation-graph science graph auto-differentiation
Language:Rust 9
codingonion / ggml-zig
[ ggml: Tensor library for machine learning ] written in zig.
ggml llama machine-learning zig large-language-models aigc llm wizardcoder chatglm chatgpt gpt4 ziglang tensor gpt auto-differentiation deep-learning
Language:Zig 7
exbibyte / dynagrad
Define-by-run arbitrary higher order autodiff for scalars in Rust. Deferred: tensor calculus implementation.
autograd auto-differentiation dynamic-computation-graphs rust
Language:Rust 7
magic3007 / AutoGrad
🎈 A C++ code generator for the automatic derivation of tensors with linear indexes. Implementation for the lesson Compiling Technology(2020 Spring, advised by Yun Liang) in Peking University.
auto-differentiation
Language:C++ 7
frasiyav / BQN-grad
Backpropagation in BQN.
auto-differentiation autograd bqn
4
oberbichler / HyperGraph
Reversed mode second order automatic differentiation for python (WIP)
automatic-differentiation auto-differentiation autodiff autodifferentiation differentiation derivatives numerical-derivation gradient hessian
Language:C++ 4
adamheins / lagrangian-mechanics-3-ways
Lagrangian mechanics implemented 3 ways: manually, with auto-diff, and symbolically.
robotics robots lagrangian-mechanics auto-differentiation symbolic-differentiation
Language:Jupyter Notebook 3
Btsan / myGradientLib
simple C++ auto-differentiation library
auto-differentiation gradient-calculation neural-network-example
Language:C++ 2
RealBunbun / dTRG
Differentiable tensor renormalization group
tensor-network auto-differentiation pytorch-implementation
Language:Python 2
yujizhu / MetaAutoDiff
MetaAutoDiff is a C++ template library for automatic differentiation in reverse mode.
template-metaprogram auto-differentiation expression-template
Language:C++ 2
alexnask / cpp_ml
C++20 machine learning library with no external dependencies (nanorange used temporarily for C++20 ranges)
auto-differentiation cpp cpp20 machine-learning
Language:C++ 1
ashwins-code / neural-network-library
Neural Network library made with numpy
machine-learning neural-network neural-networks neural-networks-from-scratch deep-learning tensors auto-differentiation
Language:Python 1
chao-ji / autograd
Library for auto differentiation based purely on NumPy
auto-differentiation autograd deep-learning-framework deep-learning-library numpy
Language:Python 1
Johnnykoch02 / MicrogradPlus
MicrogradPlus is an educational project aiming to provide a simple, yet extensible, NumPy-based automatic differentiation library.
auto-differentiation machine-learning numpy python pytorch
Language:Python 1
RAAKASH / DeepLearningFramework
This repository is an attempt to create a deep learning framework to aid in faster learning process for newbies in the deep learning field.
deep-learning-framework auto-differentiation machine-learning
Language:Jupyter Notebook 1
tsmith023 / rusty-rootsearch
A WIP library for performing multi-root searching of one-dimensional transcendental equations using auto-differentiation in Rust
auto-differentiation newtons-method rust
Language:Rust 1
rod-rom / autograd.cpp
A fast auto differentiation engine implemented in C++ 🔥
auto-differentiation cpp gradient-descent optimization
Language:C++