| Random walks on semantic networks can resemble optimal foraging JT Abbott, JL Austerweil, TL Griffiths Psychological Review 122 (3), 558-569, 2015 | 207 | 2015 |
| Evaluating (and improving) the correspondence between deep neural networks and human representations JC Peterson, JT Abbott, TL Griffiths Cognitive science 42 (8), 2648-2669, 2018 | 177 | 2018 |
| Biological origins of color categorization AE Skelton, G Catchpole, JT Abbott, JM Bosten, A Franklin Proceedings of the National Academy of Sciences 114 (21), 5545-5550, 2017 | 122 | 2017 |
| Adapting Deep Network Features to Capture Psychological Representations JC Peterson, JT Abbott, TL Griffiths Proceedings of the 38th Annual Conference of the Cognitive Science Society …, 2016 | 96 | 2016 |
| Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies Y Jia, J Abbott, J Austerweil, T Griffiths, T Darrell Advances in Neural Information Processing Systems 26, 2013 | 83 | 2013 |
| Human memory search as a random walk in a semantic network J Abbott, J Austerweil, T Griffiths Advances in Neural Information Processing Systems 25, 3050-3058, 2012 | 79* | 2012 |
| Focal colors across languages are representative members of color categories JT Abbott, TL Griffiths, T Regier Proceedings of the National Academy of Sciences 113 (40), 11178-11183, 2016 | 69 | 2016 |
| Exploring the influence of particle filter parameters on order effects in causal learning JT Abbott, TL Griffiths Proceedings of the 33rd Annual Conference of the Cognitive Science Society …, 2011 | 42 | 2011 |
| Empirical Evidence for Markov Chain Monte Carlo in Memory Search DD Bourgin, JT Abbott, TL Griffiths, KA Smith, E Vul Proceedings of the 36th Annual Conference of the Cognitive Science Society, 2014 | 38 | 2014 |
| Constructing a hypothesis space from the Web for large-scale Bayesian word learning JT Abbott, JL Austerweil, TL Griffiths Proceedings of the 34th Annual Conference of the Cognitive Science Society, 2012 | 30 | 2012 |
| Approximating Bayesian inference with a sparse distributed memory system JT Abbott, JB Hamrick, TL Griffiths Proceedings of the 35th Annual Conference of the Cognitive Science Society, 2013 | 22 | 2013 |
| Testing a Bayesian Measure of Representativeness Using a Large Image Database JT Abbott, KA Heller, Z Ghahramani, TL Griffiths Advances in Neural Information Processing Systems 24, 2321-2329, 2011 | 15 | 2011 |
| Exploring human cognition using large image databases TL Griffiths, JT Abbott, AS Hsu Topics in cognitive science 8 (3), 569-588, 2016 | 11 | 2016 |
| Predicting focal colors with a rational model of representativeness JT Abbott, T Regier, TL Griffiths Proceedings of the 34th Annual Conference of the Cognitive Science Society, 2012 | 10 | 2012 |
| Birds and Words: Exploring environmental influences on folk categorization JT Abbott, C Kemp Proceedings of the 42nd Annual Conference of the Cognitive Science Society …, 2020 | 3 | 2020 |
| Concept acquisition through meta-learning E Grant, C Finn, J Peterson, J Abbott, S Levine, T Darrell, T Griffiths NIPS Workshop on Cognitively Informed Artificial Intelligence, 34, 2017 | 3 | 2017 |
| Recommendation as Generalization: Evaluating Cognitive Models In the Wild DD Bourgin, JT Abbott, TL Griffiths Proceedings of the 40th Annual Conference of the Cognitive Science Society, 2018 | 2 | 2018 |
| Recommendation as generalization: Using big data to evaluate cognitive models. DD Bourgin, JT Abbott, TL Griffiths Journal of Experimental Psychology: General 150 (7), 1398, 2021 | 1 | 2021 |
| Visually-Grounded Bayesian Word Learning Y Jia, J Abbott, J Austerweil, T Griffiths, T Darrell EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS …, 2012 | 1 | 2012 |
| Leveraging deep neural networks to capture psychological representations JC Peterson, JT Abbott, TL Griffiths arXiv preprint arXiv:1706.02417, 2017 | | 2017 |
Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityVerified email at princeton.edu
