Automatic Differentiation: a look through Tensor and Operational Calculus

12/08/2016
by   Žiga Sajovic, et al.
0

In this paper we take a look at Automatic Differentiation through the eyes of Tensor and Operational Calculus. This work is best consumed as supplementary material for learning tensor and operational calculus by those already familiar with automatic differentiation. To that purpose, we provide a simple implementation of automatic differentiation, where the steps taken are explained in the language tensor and operational calculus.

READ FULL TEXT
research
12/08/2016

Implementing Operational calculus on programming spaces for Differentiable computing

We provide an illustrative implementation of an analytic, infinitely-dif...
research
06/03/2020

A mathematical model for automatic differentiation in machine learning

Automatic differentiation, as implemented today, does not have a simple ...
research
10/07/2020

A Simple and Efficient Tensor Calculus for Machine Learning

Computing derivatives of tensor expressions, also known as tensor calcul...
research
10/25/2016

Operational calculus on programming spaces

In this paper we develop operational calculus on programming spaces that...
research
05/06/2021

Analytical Differential Calculus with Integration

Differential lambda-calculus was first introduced by Thomas Ehrhard and ...
research
01/31/2022

Differentiating and Integrating ZX Diagrams

ZX-calculus has proved to be a useful tool for quantum technology with a...
research
09/04/2019

Automatic Differentiation for Complex Valued SVD

In this note, we report the back propagation formula for complex valued ...

Please sign up or login with your details

Forgot password? Click here to reset