Adapting deep network features to capture psychological representations: An abridged report

Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Deep neural networks have become increasingly successful at solving classic perception problems (e.g., recognizing objects), often reaching or surpassing human-level accuracy. In this abridged report of Peterson et al. [2016], we examine the relationship between the image representations learned by these networks and those of humans. We find that deep features learned in service of object classification account for a significant amount of the variance in human similarity judgments for a set of animal images. However, these features do not appear to capture some key qualitative aspects of human representations. To close this gap, we present a method for adapting deep features to align with human similarity judgments, resulting in image representations that can potentially be used to extend the scope of psychological experiments and inform human-centric AI.

Original languageEnglish (US)
Title of host publication26th International Joint Conference on Artificial Intelligence, IJCAI 2017
EditorsCarles Sierra
PublisherInternational Joint Conferences on Artificial Intelligence
Pages4934-4938
Number of pages5
ISBN (Electronic)9780999241103
StatePublished - Jan 1 2017
Externally publishedYes
Event26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, Australia
Duration: Aug 19 2017Aug 25 2017

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Other

Other26th International Joint Conference on Artificial Intelligence, IJCAI 2017
CountryAustralia
CityMelbourne
Period8/19/178/25/17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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  • Cite this

    Peterson, J. C., Abbott, J. T., & Griffiths, T. L. (2017). Adapting deep network features to capture psychological representations: An abridged report. In C. Sierra (Ed.), 26th International Joint Conference on Artificial Intelligence, IJCAI 2017 (pp. 4934-4938). (IJCAI International Joint Conference on Artificial Intelligence). International Joint Conferences on Artificial Intelligence.