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Adapting Deep Network Features to Capture Psychological Representations.

, , and . CogSci, cognitivesciencesociety.org, (2016)

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Constructing a hypothesis space from the Web for large-scale Bayesian word learning., , and . CogSci, cognitivesciencesociety.org, (2012)Empirical Evidence for Markov Chain Monte Carlo in Memory Search., , , , and . CogSci, cognitivesciencesociety.org, (2014)Random Walks on Semantic Networks Can Resemble Optimal Foraging, , and . Psychological Review, 122 (3): 558--569 (July 2015)Statistical models of learning and using semantic representations.. University of California, Berkeley, USA, (2016)base-search.net (ftcdlib:qt4f86w8q8).Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations., , and . Cogn. Sci., 42 (8): 2648-2669 (2018)Leveraging deep neural networks to capture psychological representations., , and . CoRR, (2017)Human memory search as a random walk in a semantic network., , and . NIPS, page 3050-3058. (2012)Exploring the influence of particle filter parameters on order effects in causal learning., and . CogSci, cognitivesciencesociety.org, (2011)Birds and Words: Exploring environmental influences on folk categorization., and . CogSci, cognitivesciencesociety.org, (2020)Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report., , and . IJCAI, page 4934-4938. ijcai.org, (2017)