Like automatic differentiation, but for integration
October 13, 2022
Automatic differentiation has proven its awesome utility, especially within machine learning (Baydin et al., 2018). Fasciliting the training of deep neural networks, it has become a staple of the field.
However, as far as I know, there is no analog for automatic integration. Why not? Where is it? What would it look like?
I’ll use this page collect my thoughts on the subject.
- (WIP) I try to motivate the need for automatic integration. What kind of problems could it solve? How could it be used?
- (WIP) I cover automatic differentiation and how it works.
- (WIP) A tutorial on symbolic integation and why its so hard (it’s not a closed operation).
- (WIP) An exploration of the history of integration and how it has been automated in the past.
- (WIP) A tutorial on calculus. Back to basics!
- (WIP) A literature review of recent integration ideas.
Bibliography
- Baydin, A. G., Pearlmutter, B. A., Radul, A. A., & Siskind, J. M. (2018). Automatic differentiation in machine learning: a survey. https://arxiv.org/abs/1502.05767