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# Who Invented Backpropagation?

**[Hacker News](https://daily.dev/sources/hn)** · 16 min read · 1 upvotes · 0 comments

## Summary

Backpropagation's modern version (reverse mode of automatic differentiation) was first published in 1970 by Finnish master student Seppo Linnainmaa, marking its 50th anniversary in 2020. While gradient descent concepts existed since the 1960s with work by Kelley, Bryson, and others, Linnainmaa's method provided the efficient implementation used in all modern neural network software like TensorFlow. The method was later applied to neural networks by Werbos in 1982, and gained widespread acceptance after Rumelhart et al.'s experimental analysis in 1985. Despite claims that deep networks required unsupervised pre-training, research in 2010 demonstrated that plain backpropagation could successfully train deep networks without such preprocessing.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://people.idsia.ch/~juergen/who-invented-backpropagation.html>

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Tags: [#deep-learning](https://daily.dev/tags/deep-learning), [#neural-networks](https://daily.dev/tags/neural-networks), [#gradient-descent](https://daily.dev/tags/gradient-descent)

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