tinygrad

A JavaScript/TypeScript autograd engine with operator overloading, inspired by micrograd
OpenBrowse Files
autogradneural-networkmachine-learningbackpropagationgradient-descentoperator-overloadingmicrograddeep-learningautomatic-differentiationmlp

gradiatorjs

GradiatorJS is a lightweight, from-scratch autodiff engine and a neural network library written in typescript. Featuring a powerful automatic differentiation engine using a computation graph to enable backpropagation on dynamic network architectures. You
OpenBrowse Files
neural-networkdeep-learningmachine-learningautodiffautomatic-differentiationbackpropagationgradient-descentcnnconvolutional-neural-networktypescriptjavascriptbrowserfrom-scratcheducationallightweight

@justinelliottcobb/amari-core

Advanced mathematical computing library with geometric algebra, tropical algebra, and automatic differentiation for JavaScript/TypeScript
OpenBrowse Files
wasmgeometric-algebraclifford-algebratropical-algebraautomatic-differentiationmathematicswebassemblylinear-algebramultivectorrotor

adnn.ts

adnn provides TypeSafe Javascript-native neural networks on top of general scalar/tensor reverse-mode automatic differentiation. You can use just the AD code, or the NN layer built on top of it. This architecture makes it easy to define big, complex numer
OpenBrowse Files
adnnnetwork-networkautomatic-differentiationtypescriptisomorphic

@2bad/micrograd

[![NPM version](https://img.shields.io/npm/v/@2bad/micrograd)](https://www.npmjs.com/package/@2bad/micrograd) [![License](https://img.shields.io/npm/l/@2bad/micrograd)](https://opensource.org/license/MIT) [![GitHub Build Status](https://img.shields.io/git
OpenBrowse Files
autodiffautogradautomatic-differentiationcomputational-graphmicrogradneural-network