Hopfield network/Origins

Origins of the Network edit

Ising model of a neural network as a memory model is first proposed by William A. Little in 1974,[1] which is acknowledged by Hopfield in his 1982 paper.[2] Networks with continuous dynamics were developed by Hopfield in his 1984 paper.[3] A major advance in memory storage capacity was developed by Krotov and Hopfield in 2016[4] through a change in network dynamics and energy function. This idea was further extended by Demircigil and collaborators in 2017.[5]

The continuous dynamics of large memory capacity models was developed in a series of papers between 2016 and 2020.[4][6][7] Large memory storage capacity Hopfield Networks are now called Dense Associative Memories or modern Hopfield networks.

Learning Task edit

  • Explain the role of the Energy Function for the convergence of the Hopfield networks and the recognition of trained input data for the Hopfield network.

References edit

  1. Little, W. A. (1974). "The Existence of Persistent States in the Brain". Mathematical Biosciences 19 (1–2): 101–120. doi:10.1016/0025-5564(74)90031-5. 
  2. Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences 79 (8): 2554–2558. doi:10.1073/pnas.79.8.2554. PMID 6953413. PMC 346238. //www.ncbi.nlm.nih.gov/pmc/articles/PMC346238/. 
  3. Hopfield, J. J. (1984). "Neurons with graded response have collective computational properties like those of two-state neurons". Proceedings of the National Academy of Sciences 81 (10): 3088–3092. doi:10.1073/pnas.81.10.3088. PMID 6587342. PMC 345226. //www.ncbi.nlm.nih.gov/pmc/articles/PMC345226/. 
  4. 4.0 4.1 Krotov, Dmitry; Hopfield, John (2016). "Dense Associative Memory for Pattern Recognition". Neural Information Processing Systems 29: 1172–1180. 
  5. Mete, Demircigil et al. (2017). "On a model of associative memory with huge storage capacity.". Journal of Statistical Physics 168 (2): 288–299. doi:10.1007/s10955-017-1806-y. https://link.springer.com/article/10.1007/s10955-017-1806-y. 
  6. Ramsauer, Hubert et al. (2021). "Hopfield Networks is All You Need". International Conference on Learning Representations. 
  7. Krotov, Dmitry; Hopfield, John (2021). "Large associative memory problem in neurobiology and machine learning". International Conference on Learning Representations.