The minimal representation of a system with interacting units using Boltzmann machines

Author:

Valle Mauricio A.1ORCID,Urbina Felipe2ORCID

Affiliation:

1. Facultad de Economía y Negocios, Universidad Finis Terrae, Chile

2. Centro de Investigación DAiTALab, Universidad Mayor, Chile

Publisher

ACM

Reference18 articles.

1. David  H Ackley , Geoffrey  E Hinton , and Terrence  J Sejnowski . 1985. A learning algorithm for Boltzmann machines. Cognitive science 9, 1 ( 1985 ), 147–169. David H Ackley, Geoffrey E Hinton, and Terrence J Sejnowski. 1985. A learning algorithm for Boltzmann machines. Cognitive science 9, 1 (1985), 147–169.

2. Arian Ashourvan , Preya Shah , Adam Pines , Shi Gu , Christopher  W Lynn , Danielle  S Bassett , Kathryn  A Davis , and Brian Litt . 2021. Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states. Communications biology 4, 1 ( 2021 ), 1–15. Arian Ashourvan, Preya Shah, Adam Pines, Shi Gu, Christopher W Lynn, Danielle S Bassett, Kathryn A Davis, and Brian Litt. 2021. Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states. Communications biology 4, 1 (2021), 1–15.

3. Erik Aurell and Magnus Ekeberg . 2012. Inverse Ising inference using all the data. Physical review letters 108, 9 ( 2012 ), 090201. Erik Aurell and Magnus Ekeberg. 2012. Inverse Ising inference using all the data. Physical review letters 108, 9 (2012), 090201.

4. US stock market interaction network as learned by the Boltzmann machine;Borysov S;The European Physical Journal B,2015

5. Ed Bullmore and Olaf Sporns . 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nature reviews neuroscience 10, 3 ( 2009 ), 186–198. Ed Bullmore and Olaf Sporns. 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nature reviews neuroscience 10, 3 (2009), 186–198.

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