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22 public repositories
matching this topic...
Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors
Updated
Aug 12, 2020
Python
automatic differentiation made easier for C++
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
Updated
May 5, 2019
Python
AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.
Updated
Feb 27, 2020
Python
variational quantum circuit simulator in Julia, under GPLv3
Updated
Feb 15, 2020
Julia
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Differentiable Gaussian Process implementation for PyTorch
Updated
Jul 8, 2018
Python
Updated
Dec 6, 2019
Python
Tiny calculation graph library
Updated
Jun 22, 2020
Rust
Automatic differentiation with dual numbers
MetaAutoDiff is a C++ template library for automatic differentiation in reverse mode.
🎈 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.
Reversed mode second order automatic differentiation for python (WIP)
This repository is an attempt to create a deep learning framework to aid in faster learning process for newbies in the deep learning field.
Updated
Aug 9, 2018
Jupyter Notebook
Differentiable tensor renormalization group
Updated
Dec 5, 2019
Python
simple C++ auto-differentiation library
A framework for more flexible structure of neural networks with auto-differentiation.
Updated
Feb 10, 2018
MATLAB
C++20 machine learning library with no external dependencies (nanorange used temporarily for C++20 ranges)
autoD is a lightweight, flexible automatic differentiation for python3 based on numpy.
Updated
Nov 20, 2019
Python
dynamic higher order autodiff in Rust.
This repository contains code corresponding to my blogging site.
Updated
Oct 17, 2019
Jupyter Notebook
Automatic derivative calculation of scalar functions.
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