automatic differentiation made easier for C++
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Updated
Jul 18, 2024 - C++
automatic differentiation made easier for C++
Automatic differentiation playground
A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.
An automatic differentiation library written in C++ and CUDA
Lightweight Python package for automatic differentiation
A modular C++17 framework for automatic differentiation
This is a mirror of Physica
Lightweight automatic differentiation and error propagation library
library of C++ functions that support applications of Stan in Pharmacometrics
C++ automatic differentiation library with no dependencies and arbitrary higher order derivatives, stand-alone, header only
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Reference implementation for "Temporal Set Inversion for Animated Implicits" (SIGGRAPH 2023)
Algorithmic differentiation with hyper-dual numbers in C++ and Python
This language is developed as a part of the Compilers course @ IIT Hyderabad, under Dr. Ramakrishna Upadrasta
C++20 numerical and analytical derivative computations
📍 A Swift fork working towards Enzyme integration
Yet another automatic differentiation engine to perform efficient and analytically precise partial differentiation of mathematical expressions.
An auto-differentiation engine for arbitrary tensors written from scratch in C++.
Testing capabilities of Trilinos-Sacado in combination with e. g. tensors
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