Abstract
The Thouless-Anderson-Palmer (TAP) approach was originally developed for analysing the Sherrington-Kirkpatrick model in the study of spin glass models and has been employed since then mainly in the context of extensively connected systems whereby each dynamical variable interacts weakly with the others. Recently, we extended this method for handling general intensively connected systems where each variable has only O(1) connections characterised by strong couplings. However, the new formulation looks quite different with respect to existing analyses and it is only natural to question whether it actually reproduces known results for systems of extensive connectivity. In this chapter, we apply our formulation of the TAP approach to an extensively connected system, the Hopfield associative memory model, showing that it produces identical results to those obtained by the conventional formulation.
| Original language | English |
|---|---|
| Title of host publication | Advanced mean field methods: Theory and practice |
| Editors | Manfred Opper, David Saad |
| Place of Publication | Cambridge, US |
| Publisher | MIT |
| Pages | 51-65 |
| Number of pages | 15 |
| ISBN (Print) | 0262150549 |
| Publication status | Published - Feb 2001 |
Publication series
| Name | Neural Information Processing |
|---|---|
| Publisher | Massachusetts Institute of Technology Press (MIT Press) |
Bibliographical note
Copyright of the Massachusetts Institute of Technology Press (MIT Press) Partially available on Google BooksKeywords
- Thouless-Anderson-Palmer
- Sherrington-Kirkpatrick
- general intensively connected systems
- Hopfield associative memory model
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Dive into the research topics of 'The TAP approach to intensive and extensive connectivity systems'. Together they form a unique fingerprint.Research output
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Advanced mean field methods: theory and practice
Opper, M. (Editor) & Saad, D. (Editor), Feb 2001, Cambridge, Massachusetts (US): MIT. 287 p. (Neural Information Processing)Research output: Book/Report › Book
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