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