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Automatic Differentiation in Neural Networks by Harsh Vardhan Dubey is a document available to read on EtoBox.
This document provides an introduction to automatic differentiation and neural networks. It discusses how automatic differentiation can be used to efficiently compute the gradient of neural networks during backpropagation. Specifically, it explains that automatic differentiation formalizes representing functions as expression graphs and then applying the chain rule in reverse to compute derivatives. This allows derivatives to be computed with the same time complexity as the original forward function evaluat
- Author
- Harsh Vardhan Dubey
- Language
- EN