A simple library for building computational graphs with autodiff support.
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Updated
Jul 31, 2019 - Python
A simple library for building computational graphs with autodiff support.
Realization of models from existing papers
Fork of Matt Loper's autodifferentiation framework for Python
A toy forward-mode autodiff utility written in Python
A toy deep learning framework implemented in pure Numpy from scratch. Aka homemade PyTorch lol.
Tiny automatic differentiation (autodiff) engine for NumPy tensors implemented in Python.
zapnAD: An auto-differentiation package.
Experiments with forward gradients on optimization test functions
Simple automatic differentiation implementation in python
Assignments for Data Intensive Systems for Machine Learning Coursework
Yaae: Yet another autodiff engine (written in Numpy).
Yet another tensor automatic differentiation framework
A brief (and inaccurate) history of derivatives, with a brief (and incomplete) Python implementation
Drop-in autodiff for NumPy.
Dualitic is a Python package for forward mode automatic differentiation using dual numbers.
toydl: toy deep learning algorithms implementation, backend with self implement toy torch
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
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