All Topics
Foundations
Perception
Causal Induction
Cognitive Development
Probabilistic Reasoning
Rational Process Models
Similarity and Categorization
Statistical Models of Language
Nonparametric Bayesian Models
Cultural Evolution and Iterated Learning
(Click on an author's name to view all papers by that author.)
By Sanborn, A | |
| Sanborn, A. N., Mansinghka, V. K., & Griffiths, T. L. (in press). Reconciling intuitive physics and Newtonian mechanics for colliding objects. Psychological Review. (pdf) |
| Griffiths, T. L., Vul, E., & Sanborn, A. N. (2012). Bridging levels of analysis for probabilistic models of cognition. Current Directions in Psychological Science, 21(4), 263-268. (doi) |
| Hsu, A. S., Martin, J. B., Sanborn, A. N., & Griffiths, T. L. (2012). Identifying representations of categories of discrete items using Markov chain Monte Carlo with People. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf) |
| Blundell, C., Sanborn, A. N., & Griffiths, T. L. (2012). Look-ahead Monte Carlo with people. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf) |
| Martin, J. B., Griffiths, T. L., & Sanborn, A. N. (2012). Testing the efficiency of Markov chain Monte Carlo with people using facial affect categories. Cognitive Science, 36, 150-162. (pdf) |
| Griffiths, T. L., Sanborn, A. N., Canini, K. R., Navarro, D. J., & Tenenbaum, J. B. (2011). Nonparametric Bayesian models of category learning. In E. M. Pothos & A. J. Wills (Eds.) Formal approaches in categorization. Cambridge, UK: Cambridge University Press. (book) |
| Sanborn, A. N., Griffiths, T. L., & Navarro, D. J. (2010). Rational approximations to rational models: Alternative algorithms for category learning. Psychological Review, 117 (4), 1144-1167.(pdf) |
| Shi, L., Griffiths, T. L., Feldman, N. H, & Sanborn, A. N. (2010). Exemplar models as a mechanism for performing Bayesian inference. Psychonomic Bulletin & Review, 17 (4), 443-464. (pdf) |
| Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (2010). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, 60, 63-106. (doi) |
| Sanborn, A. N., Mansinghka, V. K., & Griffiths, T. L. (2009). A Bayesian framework for modeling intuitive dynamics. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf) |
| Sanborn, A. N., & Griffiths, T. L. (2008). Markov chain Monte Carlo with people. Advances in Neural Information Processing Systems 20. (pdf) (winner of the Outstanding Student Paper prize) |
| Griffiths, T. L., Sanborn, A. N., Canini, K. R., & Navarro, D. J. (2008). Categorization as nonparametric Bayesian density estimation. In M. Oaksford and N. Chater (Eds.). The probabilistic mind: Prospects for rational models of cognition. Oxford: Oxford University Press. (manuscript pdf) |
| Griffiths, T. L., Canini, K. R., Sanborn, A. N., & Navarro, D. J. (2007) Unifying rational models of categorization via the hierarchical Dirichlet process. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (pdf) |
| Sanborn, A. N., Griffiths, T. L., & Navarro, D. J. (2006). A more rational model of categorization. Proceedings of the 28th Annual Conference of the Cognitive Science Society. (pdf) |