University of Cambridge > Talks.cam > RSE Seminars > Automatic differentiation - an RSE's eye view

Automatic differentiation - an RSE's eye view

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  • UserMatt Graham - ARC, UCL Speaker website
  • ClockThursday 20 November 2025, 13:00-14:00
  • HouseRoom A, West Hub.

If you have a question about this talk, please contact Jack Atkinson .

Automatic or algorithmic differentiation (AD) underpins much of the current boom in use of machine learning methods but is also widely used in other scientific computing contexts.

In this talk I will give an overview of what automatic differentiation is and a brief summary of its history. I will then review how it relates to symbolic and numerical differentiation, how forward- and reverse-mode AD differ and some of the different approaches to implementing AD frameworks, before demonstrating how AD is used in practice with some applied examples. I will conclude with some discussion of my experiences of using various automatic differentiation implementations in research software projects I have worked on, particularly from a context of the trade-offs between ease of use and maintainability and generality of code a framework can differentiate.

This talk is part of the RSE Seminars series.

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