Hidden Hypergraphs, Error-Correcting Codes, and Critical Learning in Hopfield Networks
In 1943, McCulloch and Pitts introduced a discrete recurrent neural network as a model for computation in brains. The work inspired breakthroughs such as the first computer design and the theory of finite automata. We focus on learning in Hopfield networks, a special case with symmetric weights and...
Main Authors: | Christopher Hillar, Tenzin Chan, Rachel Taubman, David Rolnick |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-11-01
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Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/23/11/1494 |
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