Math.NET Numerics

automatic differentiation made easier for C++

Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.

a symbolic math expression evaluator for javascript

Deep.Net machine learning framework for F#

Source Code Generation for Automatic Differentiation using Operator Overloading

clad -- automatic differentiation for C/C++

Single cell trajectory detection

➗ Library for parsing math expressions with rational numbers, finding their derivatives and compiling an optimal IL code

Implementing (parts of) TensorFlow (almost) from Scratch

xFunc is a simple and easy to use application that allows you to build mathematical and logical expressions. It's written on C#. The library includes the code that converts strings to expressions (parser, lexer and etc.)

Modern Fortran Numerical Differentiation Library

Programming language for symbolic computation with extraordinary combination of pattern matching features: Tree patterns, associative patterns and expressions embedded in patterns.

Numerical methods and exercises for Physics and Astrophysics: Integration and Differentiation,Ordinary Differential Equations, Linear Algebra and FFTs, Advection and Hyperbolic Partial Differential Equations, Elliptic Partial Differential Equations, Computational Fluid Dynamics.

eXpression differentiation in Julia

FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.

Automatic Differentiation Package for MATLAB

The one and only Golang library for single variable differentiation and integration.

Computational Graphs in R

📈 Find first derivatives of functions automagically

CASprzak is a Computer Algebra System by EasyKayzey (Erez Israeli Miller and Michael Kasprzak)

Weighted least squares meshless interpolator and differentiator.

Savitzky-Golay differentiation filters

Implementation of dual numbers for automatic differentiation of programs

A framework for multivariate functions together with constructors for schumaker splines, OLS, Chebyshev, MARS splines for approximation.

Automatic differentiation with dual numbers

Single cell trajectory detection

First- and second-order complex step derivative approximation