A Brief Introduction to Automatic Differentiation for Machine Learning

10/12/2021
by   Davan Harrison, et al.
0

Machine learning and neural network models in particular have been improving the state of the art performance on many artificial intelligence related tasks. Neural network models are typically implemented using frameworks that perform gradient based optimization methods to fit a model to a dataset. These frameworks use a technique of calculating derivatives called automatic differentiation (AD) which removes the burden of performing derivative calculations from the model designer. In this report we describe AD, its motivations, and different implementation approaches. We briefly describe dataflow programming as it relates to AD. Lastly, we present example programs that are implemented with Tensorflow and PyTorch, which are two commonly used AD frameworks.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/20/2021

Automatic Differentiation via Effects and Handlers: An Implementation in Frank

Automatic differentiation (AD) is an important family of algorithms whic...
research
10/26/2018

Automatic differentiation in ML: Where we are and where we should be going

We review the current state of automatic differentiation (AD) for array ...
research
11/07/2017

Tangent: Automatic Differentiation Using Source Code Transformation in Python

Automatic differentiation (AD) is an essential primitive for machine lea...
research
05/12/2023

Understanding Automatic Differentiation Pitfalls

Automatic differentiation, also known as backpropagation, AD, autodiff, ...
research
04/04/2023

Automatic Differentiation of Binned Likelihoods With Roofit and Clad

RooFit is a toolkit for statistical modeling and fitting used by most ex...
research
10/16/2022

Automatic Differentiation of Programs with Discrete Randomness

Automatic differentiation (AD), a technique for constructing new program...
research
04/02/2018

The simple essence of automatic differentiation

Automatic differentiation (AD) in reverse mode (RAD) is a central compon...

Please sign up or login with your details

Forgot password? Click here to reset