Tensor library for machine learning
-
Updated
Dec 18, 2024 - C++
Tensor library for machine learning
Gorgonia is a library that helps facilitate machine learning in Go.
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Source-to-Source Debuggable Derivatives in Pure Python
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
Self-contained Machine Learning and Natural Language Processing library in Go
automatic differentiation made easier for C++
The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
21st century AD
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
High-performance automatic differentiation of LLVM and MLIR.
Owl - OCaml Scientific Computing @ https://ocaml.xyz
Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
A JavaScript library like PyTorch, with GPU acceleration.
Forward Mode Automatic Differentiation for Julia
OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions
A simple library for creating complex neural networks
Aircraft design optimization made fast through computational graph transformations (e.g., automatic differentiation). Composable analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)
Add a description, image, and links to the automatic-differentiation topic page so that developers can more easily learn about it.
To associate your repository with the automatic-differentiation topic, visit your repo's landing page and select "manage topics."