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.)
By Tenenbaum, J. | |
| Kemp, C., Tenenbaum, J.B., Niyogi, S., & Griffiths, T. L. (in press). A probabilistic model of theory formation. Cognition. (doi) |
| Griffiths, T. L., & Tenenbaum, J. B. (2009). Theory-based causal induction. Psychological Review, 116, 661-716. (pdf) |
| Vul, E., Goodman, N. D., Griffiths, T. L., & Tenenbaum, J. B. (2009). One and done? Optimal decisions from very few samples. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf) |
| Dowman, M., Savova, V., Griffiths, T. L., Kording, K. P., Tenenbaum, J. B., Purver, M. (2008). A probabilistic model of meetings that combines words and discourse features. IEEE Transactions on Audio, Speech, and Language Processing, 16, 1238-1248. (pdf) |
| 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) |
| 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) |
| Griffiths, T. L., Kemp, C., & Tenenbaum, J. B. (2008). Bayesian models of cognition. In Ron Sun (ed.), The Cambridge handbook of computational cognitive modeling. Cambridge 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) |
| Frank, M. C., Goldwater, S., Mansinghka, V., Griffiths, T., & Tenenbaum, J. (2007). Modeling human performance in statistical word segmentation. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (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., Steyvers, M., & Tenenbaum, J. B. (2007). Topics in semantic representation. Psychological Review, 114,211-244. (pdf) (topic modeling toolbox) |
| Tenenbaum, J. B., Griffiths, T. L., & Niyogi, S. (2007). Intuitive theories as grammars for causal inference. In A. Gopnik, & L. Schulz (Eds.), Causal learning: Psychology, philosophy, and computation. Oxford: Oxford University Press. (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2007). Two proposals for causal grammars. In A. Gopnik & L. Schulz (Eds.), Causal learning: Psychology, philosophy, and computation. Oxford: Oxford University Press. (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2007). From mere coincidences to meaningful discoveries. Cognition, 103, 180-226. (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2006). Optimal predictions in everyday cognition. Psychological Science, 17, 767-773. (pdf) (article in The Economist) |
| Tenenbaum, J. B., Griffiths, T. L., & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Science, 10, 309-318. (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2006). Statistics and the Bayesian mind. Significance, 3, 130-133. (pdf) |
| Purver, M., Kording, K. P., Griffiths, T. L., & Tenenbaum, J. B. (2006). Unsupervised topic modelling for multi-party spoken discourse. Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. (pdf) |
| Kemp, C., Tenenbaum, J. B., Griffiths, T. L., Yamada, T., & Ueda, N. (2006). Learning systems of concepts with an infinite relational model. Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI '06). (pdf) (IRM code) |
| Mansinghka, V. K., Kemp, C., Tenenbaum, J. B., & Griffiths, T. L. (2006). Structured priors for structure learning. Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI 2006). (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2005). Structure and strength in causal induction. Cognitive Psychology, 51, 354-384. (pdf) (Matlab code for computing causal support) |
| Iwata, T., Saito, K., Ueda, N., Stromsten, S., Griffiths, T. L., & Tenenbaum, J. B. (2005). Parametric embedding for class visualization. Advances in Neural Information Processing Systems 17. (pdf) |
| Griffiths, T. L., Steyvers, M., Blei, D. M., & Tenenbaum, J. B. (2005). Integrating topics and syntax. Advances in Neural Information Processing Systems 17. (pdf) (topic modeling toolbox) |
| Kemp, C., Griffiths, T. L., & Tenenbaum, J. B. (2004). Discovering latent classes in relational data. AI Memo 2004-019 (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) |
| Blei, D.M., Griffiths, T. L., Jordan, M. I., & Tenenbaum, J. B. (2004). Hierarchical topic models and the nested Chinese restaurant process. Advances in Neural Information Processing Systems 16. (pdf) (winner of the Best Student Paper prize) |
| Griffiths, T. L., & Tenenbaum, J. B. (2004). From algorithmic to subjective randomness. Advances in Neural Information Processing Systems 16. (pdf) (winner of the Best Student Paper prize) |
| Griffiths, T. L., Baraff, E.R., & Tenenbaum, J. B. (2004). Using physical theories to infer hidden causal structure. Proceedings of the 26th Annual Conference of the Cognitive Science Society. (pdf) |
| Danks, D., Griffiths, T. L., & Tenenbaum, J. B. (2003). Dynamical causal learning. Advances in Neural Information Processing Systems 15. (pdf) |
| Tenenbaum, J. B., & Griffiths, T. L. (2003). Theory-based causal inference. Advances in Neural Information Processing Systems 15. (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2003). Probability, algorithmic complexity, and subjective randomness. Proceedings of the 25th Annual Conference of the Cognitive Science Society. (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2002). Using vocabulary knowledge in Bayesian multinomial estimation. Advances in Neural Information Processing Systems 14. (pdf) |
| Tenenbaum, J. B., & Griffiths, T. L. (2001). Structure learning in human causal induction. Advances in Neural Information Processing Systems 13. (pdf) (Matlab code for computing causal support) |
| Griffiths, T. L., & Tenenbaum, J. B. (2001). Randomness and coincidences: Reconciling intuition and probability theory. Proceedings of the 23rd Annual Conference of the Cognitive Science Society. (pdf) |
| Tenenbaum, J. B., & Griffiths, T. L. (2001). The rational basis of representativeness. Proceedings of the 23rd Annual Conference of the Cognitive Science Society. (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) |
| Griffiths, T. L., & Tenenbaum, J. B. (2000). Teacakes, trains, toxins, and taxicabs: A Bayesian account of predicting the future. Proceedings of the 22nd Annual Conference of the Cognitive Science Society. (pdf) |