All Topics
Foundations
Causal Induction
Probabilistic Reasoning
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.)
Similarity and Categorization | |
| Xu, J., & Griffiths, T. L. (in press). A rational analysis of the effects of memory biases on serial reproduction. Cognitive Psychology. (doi) |
| Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (in press). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology. (doi) |
| Feldman, N. H., Griffiths, T. L., & Morgan, J. L. (2009). The influence of categories on perception: Explaining the perceptual magnet effect as optimal statistical inference. Psychological Review, 116, 752-782. (pdf) |
| Austerweil, J. L., & Griffiths, T. L. (2009). The effect of distributional information on feature learning. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf) |
| Griffiths, T. L., Lucas, C., Williams, J. J., & Kalish, M. L. (2009). Modeling human function learning with Gaussian processes. Advances in Neural Information Processing Systems 21. (pdf) |
| Xu, J., & Griffiths, T. L. (2009). How memory biases affect information transmission: A rational analysis of serial reproduction. Advances in Neural Information Processing Systems 21. (pdf) |
| Austerweil, J., & Griffiths, T. L. (2009). Analyzing human feature learning as nonparametric Bayesian inference. Advances in Neural Information Processing Systems 21. (pdf) |
| Austerweil, J., & Griffiths, T. L. (2008). A rational analysis of confirmation with deterministic hypotheses. Proceedings of the 30th Annual Conference of the Cognitive Science Society. (pdf) |
| Shi, L., Feldman, N. H., & Griffiths, T. L. (2008). Performing Bayesian inference with exemplar models. Proceedings of the 30th 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) |
| Navarro, D. J., & Griffiths, T. L. (2008). Latent features in similarity judgment: A nonparametric Bayesian approach. Neural Computation, 20, 2597-2628.(pdf) |
| Griffiths, T. L., Christian, B. R., & Kalish, M. L. (2008). Using category structures to test iterated learning as a method for revealing inductive biases. Cognitive Science, 32, 68-107. (doi) |
| Goodman, N. D., Tenenbaum, J. B., Feldman, J., & Griffiths, T. L. (2008). A rational analysis of rule-based concept learning. Cognitive Science, 32, 108-154. (doi) |
| 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) |
| Goodman, N. D., Tenenbaum, J. B., Griffiths, T. L., & Feldman, J. (2008). Compositionality in rational analysis: Grammar-based induction for concept learning. In M. Oaksford and N. Chater (Eds.). The probabilistic mind: Prospects for rational models of cognition. Oxford: Oxford University Press. (manuscript pdf) |
| Iwata, T., Saito, K., Ueda, N., Stromsten, S., Griffiths, T. L., & Tenenbaum, J. B. (2007). Parametric embedding for class visualization. Neural Computation, 19, 2536-2556. (pdf) |
| Goodman, N. D., Griffiths, T. L., Feldman, J., & Tenenbaum, J. B. (2007). A rational analysis of rule-based concept learning. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (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) |
| Feldman, N. H., & Griffiths, T. L. (2007). A rational account of the perceptual magnet effect. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (pdf) |
| Navarro, D. J., & Griffiths, T. L. (2007). A nonparametric Bayesian method for inferring features from similarity judgments. Advances in Neural Information Processing Systems 19. (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) |
| Griffiths, T. L., Christian, B. R., & Kalish, M. L. (2006). Revealing priors on category structures through iterated learning. Proceedings of the 28th Annual Conference of the Cognitive Science Society. (pdf) |
| Kemp, C. S., Griffiths, T. L., Stromsten, S., & Tenenbaum, J. B. (2004). Semi-supervised learning with trees. Advances in Neural Information Processing Systems 16. (pdf) |
| Griffiths, T. L., & Kalish, M. L. (2002). A multidimensional scaling approach to mental multiplication. Memory and Cognition, 30, 97-106. (pdf) |
| Tenenbaum, J. B., & Griffiths, T. L. (2001). Generalization, similarity, and Bayesian inference. Behavioral and Brain Sciences, 24,629-641. (pdf) |
| Tenenbaum, J. B., & Griffiths, T. L. (2001). Some specifics about generalization. Behavioral and Brain Sciences, 24, 772-778. (html) |
| Lewandowsky, S., Kalish, M., & Griffiths, T. L. (2000). Competing strategies in categorization: Expediency and resistance to knowledge restructuring. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 1666-1684. (pdf) |