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.)
Rational Process Models | |
| Abbott, J. T., Hamrick, J. B., & Griffiths, T. L. (in press). Approximating Bayesian inference with a sparse distributed memory system. Proceedings of the 35th Annual Conference of the Cognitive Science Society. (pdf) |
| Denison, S., Bonawitz, E., Gopnik, A., & Griffiths, T. L. (in press). Rational variability in children's causal inferences: The Sampling Hypothesis. Cognition. (doi) |
| Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2013). Human memory search as a random walk in a semantic network. Advances in Neural Information Processing Systems, 25. (pdf) |
| Lieder, F., Griffiths, T. L., & Goodman, N. D. (2013). Burn-in, bias, and the rationality of anchoring. Advances in Neural Information Processing Systems, 25. (pdf) |
| Bonawitz, E., Gopnik, A., Denison, S., & Griffiths, T. L. (2012). Rational randomness: The role of sampling in an algorithmic account of preschoolers' causal learning. In F. Xu (Ed.) Rational constructivism in cognitive development. Waltham, MA: Academic Press. (book) |
| 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) |
| Abbott, J. T., & Griffiths, T. L. (2011). Exploring the influence of particle filter parameters on order effects in causal learning. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (pdf) |
| Bonawitz, E., Denison, S., Chen, A., Gopnik, A., & Griffiths, T. L. (2011). A simple sequential algorithm for approximating Bayesian inference. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (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) |
| Bonawitz, E. B., & Griffiths, T. L. (2010). Deconfounding hypothesis generation and evaluation in Bayesian models. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf) |
| Denison, S., Bonawitz, E. B., Gopnik, A., & Griffiths, T. L. (2010). Preschoolers sample from probability distributions. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf) |
| Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (2010). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, 60, 63-106. (doi) |
| Shi, L., & Griffiths, T. L. (2009). Neural implementation of hierarchical Bayesian inference by importance sampling. Advances in Neural Information Processing Systems 22. (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) |
| Levy, R., Reali, F., & Griffths, T. L. (2009). Modeling the effects of memory on human online sentence processing with particle filters. Advances in Neural Information Processing Systems 21. (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., & Navarro, D. J. (2006). A more rational model of categorization. Proceedings of the 28th Annual Conference of the Cognitive Science Society. (pdf) |