Abstract
Integrated information and variational inference provide influential mathematical frameworks in neuroscience. Yet, the understanding of the connection between the two is limited. Here, we study a minimal model to show how variational inference displays large integrated information for highly correlated target distributions, in contrast with alternative inference approaches like maximum likelihood estimation.
Issue Section:
General Conference
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© 2023 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
2023
Massachusetts Institute of Technology
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.
Issue Section:
General Conference