Abstract
Energy-based models are a specific class of neural networks. The simplest energy model is the Hopfield Network dating back from the 1980s (Hopfield Proc Nat Acad Sci USA 79(8):2554–2558, 1982, [1]). Hopfield networks are often thought to be very simple, but they are quite different from what we have seen before.
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Notes
- 1.
For a fully detailed view, see the blog entry of one of the creators of the NTM, https://medium.com/aidangomez/the-neural-turing-machine-79f6e806c0a1.
- 2.
By default, memory networks make one hop, but it has been shown that multiple hops are beneficial, especially in natural language processing.
- 3.
Winograd sentences are sentences of a particular form, whare the computer should resolve the coreference of a pronoun. They were proposed as an alternative to the Turing test, since the turing test has some deep flaws (deceptive behaviour is encouraged), and it is hard to quantify its results and evaluate it on a large scale. Winograd sentences are sentances of the form ‘I tried to put the book in the drwer but it was too [big/small]’, and they are named after Terry Winograd who first considered them in the 1970s [13].
References
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Skansi, S. (2018). An Overview of Different Neural Network Architectures. In: Introduction to Deep Learning. Undergraduate Topics in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-73004-2_10
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