Exploring the influence of particle filter parameters on order effects in causal learning. - Joshua T. Abbott; Thomas L. Griffiths 001 (CogSci, 2011)

Testing a Bayesian Measure of Representativeness Using a Large Image Database. - Joshua T. Abbott; Katherine A. Heller; Zoubin Ghahramani; Thomas L. Griffiths 001 (NIPS, 2011)

Constructing a hypothesis space from the Web for large-scale Bayesian word learning. - Joshua T. Abbott; Joseph L. Austerweil; Thomas L. Griffiths 001 (CogSci, 2012)

Predicting focal colors with a rational model of representativeness. - Joshua T. Abbott; Terry Regier; Thomas L. Griffiths 001 (CogSci, 2012)

Human memory search as a random walk in a semantic network. - Joshua T. Abbott; Joseph L. Austerweil; Thomas L. Griffiths 001 (NIPS, 2012)

Approximating Bayesian inference with a sparse distributed memory system. - Joshua T. Abbott; Jessica B. Hamrick; Thomas L. Griffiths 001 (CogSci, 2013)

Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies. - Yangqing Jia; Joshua T. Abbott; Joseph L. Austerweil; Thomas L. Griffiths 001; Trevor Darrell (NIPS, 2013)

Empirical Evidence for Markov Chain Monte Carlo in Memory Search. - David Bourgin; Joshua T. Abbott; Thomas L. Griffiths 001; Kevin A. Smith 001; Ed Vul (CogSci, 2014)

Adapting Deep Network Features to Capture Psychological Representations. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (CogSci, 2016)

Exploring Human Cognition Using Large Image Databases. - Thomas L. Griffiths 001; Joshua T. Abbott; Anne S. Hsu (Top. Cogn. Sci., 2016)

Statistical models of learning and using semantic representations. - Joshua T. Abbott (2016)

Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (IJCAI, 2017)

Leveraging deep neural networks to capture psychological representations. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (CoRR, 2017)

Recommendation as Generalization: Evaluating Cognitive Models In the Wild. - David Bourgin; Joshua T. Abbott; Tom Griffiths 001 (CogSci, 2018)

Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (Cogn. Sci., 2018)

Birds and Words: Exploring environmental influences on folk categorization. - Joshua T. Abbott; Charles Kemp (CogSci, 2020)