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 Griffiths, T | |
| Rafferty, A. N., Griffiths, T. L., & Ettlinger, M. (in press). Greater learnability is not sufficient to produce cultural universals. Cognition. (pdf) |
| 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) |
| Hu, J. C., Buchsbaum, D., Griffiths, T. L., & Xu, F. (in press). When does the majority rule? Preschoolers' trust in majority informants varies by task domain. Proceedings of the 35th Annual Conference of the Cognitive Science Society. (pdf) |
| Whalen, A., Buchsbaum, D., & Griffiths, T. L. (in press). How do you know that? Sensitivity to statistical dependency in social learning. Proceedings of the 35th Annual Conference of the Cognitive Science Society. (pdf) |
| Feldman, N. H., Myers, E. B., White, K. S., Griffiths, T. L., & Morgan, J. L. (in press). Word-level information influences phonetic learning in adults and infants. Cognition. (pdf) |
| Williams, J. J., & Griffiths, T. L. (in press). Why are people bad at detecting randomness? A statistical argument. Journal of Experimental Psychology: Learning, Memory & Cognition. (pdf) |
| Sanborn, A. N., Mansinghka, V. K., & Griffiths, T. L. (in press). Reconciling intuitive physics and Newtonian mechanics for colliding objects. Psychological Review. (pdf) |
| Schlerf, J., Xu, J., Klemfuss, N., Griffiths, T. L., & Ivry, R. B. (in press). Individuals with cerebellar degeneration show similar adaptation deficits with large and small visuomotor errors. Journal of Neurophysiology. (pdf) |
| Griffiths, T. L., Lewandowsky, S., & Kalish, M. L. (in press). The effects of cultural transmission are modulated by the amount of information transmitted. Cognitive Science. (pdf) |
| Denison, S., Bonawitz, E., Gopnik, A., & Griffiths, T. L. (in press). Rational variability in children's causal inferences: The Sampling Hypothesis. Cognition. (doi) |
| Xu, J., Dowman, M., & Griffiths, T. L. (2013) Cultural transmission results in convergence towards colour term universals. Proceedings of the Royal Society, Series B. (doi) |
| Bouchard-Cote, A., Hall, D., Griffiths, T. L., & Klein, D. (2013) Automated reconstruction of ancient languages using probabilistic models of sound change. Proceedings of the National Academy of Sciences. (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) |
| Bugnyar, T., Boyd, R., Bossan, B., Gächter, S., Griffiths, T., Hammerstein, P., Jensen, K., Mussweiler, T., Nagel, R., & Warneken, F. (2012). Evolutionary perspectives on social cognition. In P. Hammerstein & J. R. Stevens (Eds.) Evolution and the Mechanisms of Decision Making: Toward a Darwinian Decision Theory. Cambridge, MA: MIT Press. (book) |
| 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., Tenenbaum, J. B., & Kemp, C. (2012). Bayesian inference. In K. J. Holyoak & R. G. Morrison, (Eds.) Oxford Handbook of Thinking and Reasoning. Oxford: Oxford University Press. (book) |
| Griffiths, T. L., Chater, N., Norris, D., & Pouget, A. (2012). How the Bayesians got their beliefs (and what those beliefs actually are). Psychological Bulletin, 138, 415-422. (doi) |
| Griffiths, T. L., & Austerweil, J. L. (2012). Bayesian generalization with circular consequential regions. Journal of Mathematical Psychology, 56, 281-285. (doi) |
| 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) |
| Buchsbaum, D., Bridgers, S., Whalen, A., Seiver, E., Griffiths, T. L., & Gopnik, A. (2012). Do I know that you know what you know? Modeling testimony in causal inference. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf) |
| 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) |
| Rafferty, A. N., Zaharia, M., & Griffiths, T. L. (2012). Optimally Designing Games for Cognitive Science Research. 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) |
| Little, D., Lewandowsky, S., & Griffiths, T. L. (2012). A Bayesian model of rule induction in Raven's progressive matrices. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf) |
| Griffiths, T. L., Austerweil, J. L., & Berthiaume, V. G. (2012). Comparing the inductive biases of simple neural networks and Bayesian models. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf) |
| Abbott, J. T., Regier, T., & Griffiths, T. L. (2012). Predicting focal colors with a rational model of representativeness. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf) |
| Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2012). Constructing a hypothesis space from the Web for large-scale Bayesian word learning. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf) |
| Pacer, M., & Griffiths, T. L. (2012). Elements of a rational framework for continuous-time causal induction. 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) |
| Austerweil, J. L., & Griffiths, T. L. (2012). Human feature learning. Encyclopedia of the sciences of learning. N.M. Seel, ed. New York: Springer. (book) |
| Griffiths, T. L., & Tenenbaum, J.B. (2011). Predicting the future as Bayesian inference: People combine prior knowledge with observations when estimating duration and extent. Journal of Experimental Psychology: General, 140, 725-743. (pdf) |
| Griffiths, T. L., Sobel, D., Tenenbaum, J. B., & Gopnik, A. (2011). Bayes and blickets: Effects of knowledge on causal induction in children and adults. Cognitive Science, 35, 1407-1455. (pdf) |
| Austerweil, J. L., Friesen, A. L., & Griffiths, T. L. (2011). An ideal observer model for identifying the reference frame of objects. Advances in Neural Information Processing Systems, 24. (pdf) |
| Abbott, J. T., Heller, K. A., Ghahramani, Z., & Griffiths, T. L. (2011). Testing a Bayesian measure of representativeness using a large image database. Advances in Neural Information Processing Systems, 24. (pdf) |
| Pacer, M., & Griffiths, T. L. (2011). A rational model of causal induction with continuous causes. Advances in Neural Information Processing Systems, 24. (pdf) |
| Austerweil, J. L., & Griffiths, T. L. (2011). A rational model of the effects of distributional information on feature learning. Cognitive Psychology, 63, 173-209. (doi) |
| Goldwater, S., Griffiths, T. L., Johnson, M. (2011). Producing power-law distributions and damping word frequencies with two-stage language models. Journal of Machine Learning Research, 12, 2335-2382. (pdf) |
| Feldman, N. H., Myers, E., White, K., Griffiths, T. L., & Morgan, J. L. (2011). Learners use word-level statistics in phonetic category acquisition. Proceedings of the 35th Boston University Conference on Language Development. (pdf) |
| Perfors, A., Tenenbaum, J.B., Griffiths, T. L., & Xu, F. (2011). A tutorial introduction to Bayesian models of cognitive development. Cognition, 120, 302-321. (pdf) |
| Buchsbaum, D., Gopnik, A., Griffiths, T. L., & Shafto, P. (2011). Children's imitation of causal action sequences is influenced by statistical and pedagogical evidence. Cognition, 120, 331-340. (pdf) |
| Austerweil, J. L., & Griffiths, T. L. (2011). Seeking confirmation is rational for deterministic hypotheses. Cognitive Science, 35, 499-526. (pdf) |
| Griffiths, T. L., & Ghahramani, Z. (2011). The Indian Buffet Process: An introduction and review. Journal of Machine Learning Research, 12, 1185-1224. (pdf) |
| Griffiths, T. L., & Reali, F. (2011). Modelling minds as well as populations. Proceedings of the Royal Society, Series B. (pdf) |
| Rafferty, A. N., Brunskill, E.B., Griffiths, T. L., & Shafto, P. (2011). Faster teaching by POMDP planning. Proceedings of the 15th International Conference on Artificial Intelligence in Education (AIED2011). (pdf) |
| Canini, K. R., & Griffiths, T. L. (2011). A nonparametric Bayesian model of multi-level category learning. Proceedings of the 25th AAAI Conference on Artificial Intelligence.(pdf) |
| Yeung, S., & Griffiths, T. L. (2011). Estimating human priors on causal strength. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (pdf) |
| Canini, K. R., Griffiths, T. L., Vanpaemel, W., & Kalish, M. L. (2011). Discovering inductive biases in categorization through iterated learning. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (pdf) |
| 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) |
| Waisman, A. S., Lucas, C. G., Griffiths, T. L., Jacobs, L. F. (2011). A Bayesian model of navigation in squirrels. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (pdf) |
| Buchsbaum, D., Canini, K. R., and Griffiths, T. L. (2011). Segmenting and recognizing human action using low-level video features. Proceedings of the 33rd Annual Conference of the Cognitive Science Society.(pdf) |
| Rafferty, A. N., Griffiths, T. L., & Ettlinger, M. (2011) Exploring the relationship between learnability and linguistic universals. Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics at ACL 2011. (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) |
| 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) |
| Griffiths, T. L. (2011). Rethinking language: How probabilities shape the words we use. Proceedings of the National Academy of Sciences, 108, 3825-3826. (doi) |
| Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011) How to grow a mind: Statistics, structure, and abstraction. Science, 331, 1279-1285. (doi) |
| Frank, M., Goldwater, S., Griffiths, T. L., & Tenenbaum , J. B. (2010). Modeling human performance in statistical word segmentation. Cognition, 117, 107-125.(pdf) |
| 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) |
| Austerweil, J. L., & Griffiths, T. L. (2010). Learning invariant features using the Transformed Indian Buffet Process. Advances in Neural Information Processing Systems 23. (pdf) |
| Hsu, A., Griffiths, T. L., & Schreiber, E. (2010). Subjective randomness and natural scene statistics. Psychonomic Bulletin & Review, 17, 624-629. (pdf) |
| Griffiths, T. L., Chater, N., Kemp, C., Perfors, A., & Tenenbaum, J. B. (2010). Probabilistic models of cognition: Exploring representations and inductive biases. Trends in Cognitive Sciences, 14, 357-364. (pdf) |
| Xu, J., Griffiths, T. L., & Dowman, M. (2010). Replicating color term universals through human iterated learning. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf) |
| Hsu, A. S., & Griffiths, T. L. (2010). Effects of generative and discriminative learning on use of category variability. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf) |
| Rafferty, A. N., & Griffiths, T. L. (2010). Optimal language learning: The importance of starting representative. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf) |
| Buchsbaum, D., Gopnik, A., & Griffiths, T. L. (2010). Children's imitation of action sequences is influenced by statistical evidence and inferred causal structure. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (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) |
| Austerweil, J. L., & Griffiths, T. L. (2010). Learning hypothesis spaces and dimensions through concept learning. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf) |
| Lucas, C. G., Gopnik, A., & Griffiths, T. L. (2010). Developmental differences in learning the forms of causal relationships. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf) |
| Canini, K. R., Shashkov, M. M., & Griffiths, T. L. (2010). Modeling transfer learning in human categorization with the hierarchical Dirichlet process. Proceedings of the 27th International Conference on Machine Learning. (pdf) |
| Rosen-Zvi, M., Chemudugunta, C., Griffiths, T. L., Smyth, P., & Steyvers, M. (2010). Learning author-topic models from text corpora. ACM Transactions on Information Systems, 28(1), Article 4. (pdf) |
| Griffiths, T. L. (2010). Bayesian models as tools for exploring inductive biases. In M. Banich & D. Caccamise (Eds.) Generalization of knowledge: Multidisciplinary perspectives. New York: Psychology Press. (book) |
| Burkett, D., & Griffiths, T. L. (2010). Iterated learning of multiple languages from multiple teachers. Evolang 8. (pdf) |
| Blei, D. M., Griffiths, T. L., & Jordan, M. I. (2010). The nested Chinese restaurant process and Bayesian nonparametric inference of topic hierarchies. Journal of the ACM, 57, 1-30.(pdf) |
| Reali, F., & Griffiths, T. L. (2010). Words as alleles: Connecting language evolution with Bayesian learners to models of genetic drift. Proceedings of the Royal Society, Series B, 277, 429-436. (doi) |
| Kemp, C., Tenenbaum, J.B., Niyogi, S., & Griffiths, T. L. (2010). A probabilistic model of theory formation. Cognition, 114, 165-196. (doi) |
| Lucas, C. G., & Griffiths, T. L. (2010). Learning the form of causal relationships using hierarchical Bayesian models. Cognitive Science, 34, 113-147. (pdf) |
| Xu, J., & Griffiths, T. L. (2010). A rational analysis of the effects of memory biases on serial reproduction. Cognitive Psychology, 60, 107-126. (doi) |
| Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (2010). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, 60, 63-106. (doi) |
| Hsu, A., & Griffiths, T. L. (2009). Differential use of implicit negative evidence in generative and discriminative language learning. Advances in Neural Information Processing Systems 22. (pdf) |
| Miller, K. T., Griffiths, T. L., & Jordan, M. I. (2009). Nonparametric latent feature models for link prediction. Advances in Neural Information Processing Systems 22. (pdf) |
| Shi, L., & Griffiths, T. L. (2009). Neural implementation of hierarchical Bayesian inference by importance sampling. Advances in Neural Information Processing Systems 22. (pdf) |
| Lewandowsky, S., Griffiths, T. L., & Kalish, M. L. (2009). The wisdom of individuals: Exploring peoples knowledge about everyday events using iterated learning. Cognitive Science, 33, 969-998. (pdf) |
| 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) |
| Griffiths, T. L., & Tenenbaum, J. B. (2009). Theory-based causal induction. Psychological Review, 116, 661-716. (pdf) |
| Jaeger, H., Baronchelli, A., Briscoe, T., Christiansen, M. H., Griffiths, T., Jager, G., Kirby, S., Komarova, N. L., Richerson, P. J., Steels, L., & Triesch, J. (2009). What can mathematical, computational and robotic models tell us about the origins of syntax? In D. Bickerton & E. Szathmary (Eds.) Biological foundations and origins of syntax. Cambridge, MA: MIT Press. (book) |
| Griffiths, T.L. (2009). Connecting human and machine learning via probabilistic models of cognition. InterSpeech 2009. (pdf) |
| Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian framework for word segmentation: Exploring the effects of context. Cognition, 112, 21-54. (pdf) |
| Reali, F., & Griffiths, T. L. (2009). The evolution of linguistic frequency distributions: Relating regularization to inductive biases through iterated learning. Cognition, 111, 317-328. (pdf) |
| 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) |
| 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) |
| 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) |
| Beppu, A., & Griffiths, T. L. (2009). Iterated learning and the cultural ratchet. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf) |
| Buchsbaum, D., Griffiths, T. L., Gopnik, A., & Baldwin, D. (2009). Learning from actions and their consequences: Inferring causal variables from continuous sequences of human action. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf) |
| Feldman, N. H., Griffiths, T. L., & Morgan, J. L. (2009). Learning phonetic categories by learning a lexicon. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf) |
| Rafferty, A., Griffiths, T. L., & Klein, D. (2009). Convergence bounds for language evolution by iterated learning. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf) |
| Bouchard-Cote, A., Griffiths, T. L., & Klein, D. (2009). Improved reconstruction of protolanguage word forms. Proceedings of the North American Conference on Computational Linguistics (NAACL'09). (pdf) |
| Canini, K. R., Shi, L., & Griffiths, T. L. (2009). Online inference of topics with Latent Dirichlet Allocation. AISTATS. (pdf) |
| Lucas, C., Griffiths, T. L., Xu, F., & Fawcett, C. (2009). A rational model of preference learning and choice prediction by children. Advances in Neural Information Processing Systems 21. (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) |
| 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) |
| Griffiths, T. L., Kalish, M. L., & Lewandowsky, S. (2008). Theoretical and experimental evidence for the impact of inductive biases on cultural evolution. Philosophical Transactions of the Royal Society, 363, 3503-3514. (pdf) |
| Smith, K., Kalish, M. L., Griffiths, T. L., & Lewandowsky, S. (2008). Cultural transmission and the evolution of human behaviour. Philosophical Transactions of the Royal Society, 363, 3469-3476. (pdf) |
| Miller, K. T., Griffiths, T. L., & Jordan, M. I. (2008). The phylogenetic Indian buffet process: A non-exchangeable nonparametric prior for latent features.Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI 2008). (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) |
| Reali, F., & Griffiths, T. L. (2008). The evolution of frequency distributions: Relating regularization to inductive biases through iterated learning. 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) |
| Williams, J. J., & Griffiths, T. L. (2008). Why are people bad at detecting randomness? Because it is hard. Proceedings of the 30th Annual Conference of the Cognitive Science Society. (pdf) |
| Xu, J., Reali, F., & Griffiths, T. L. (2008). A formal analysis of cultural evolution by replacement. 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) |
| Bouchard-Cote, A., Liang, P., Griffiths, T. L., & Klein, D. (2008). A probabilistic approach to language change. Advances in Neural Information Processing Systems 20. (pdf) |
| 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) |
| Steyvers, M., & Griffiths, T. L. (2008). Rational analysis as a link between human memory and information retrieval. 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., & Yuille, A. (2008). A primer on probabilistic inference. 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) |
| Griffiths, T. L., Steyvers, M., & Firl, A. (2007). Google and the mind: Predicting fluency with PageRank. Psychological Science, 18, 1069-1076. (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) |
| Schulz, L.E., Bonawitz, E. B., & Griffiths, T. L. (2007). Can being scared make your tummy ache? Naive theories, ambiguous evidence and preschoolers' causal inferences. Developmental Psychology, 43, 1124-1139. (pdf) |
| Bouchard, A., Liang, P., Griffiths, T., & Klein, D. (2007). A probabilistic approach to diachronic phonology. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). (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., 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) |
| Schreiber, E., & Griffiths, T. L. (2007) Subjective randomness and natural scene statistics. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (pdf) |
| Wood, F., & Griffiths, T. L. (2007). Particle filtering for nonparametric Bayesian matrix factorization. Advances in Neural Information Processing Systems 19. (pdf) |
| Johnson, M., Griffiths, T. L., & Goldwater, S. (2007). Adaptor grammars: A framework for specifying compositional nonparametric Bayesian models. Advances in Neural Information Processing Systems 19. (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) |
| Griffiths, T. L., & Kalish, M. L. (2007). Language evolution by iterated learning with Bayesian agents. Cognitive Science, 31, 441-480. (pdf) |
| Kalish, M. L., Griffiths, T. L., & Lewandowsky, S. (2007). Iterated learning: Intergenerational knowledge transmission reveals inductive biases. Psychonomic Bulletin and Review, 14, 288-294. (pdf) |
| Goldwater, S., & Griffiths, T. L. (2007). A fully Bayesian approach to unsupervised part-of-speech tagging. Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL'07). (pdf) |
| Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007). Topics in semantic representation. Psychological Review, 114,211-244. (pdf) (topic modeling toolbox) |
| Ghahramani, Z., Griffiths, T. L., & Sollich, P. (2007). Bayesian nonparametric latent feature models. Bayesian Statistics 8. Oxford University Press. (pdf) (discussion) (rejoinder) |
| Johnson, M., Griffiths, T. L., & Goldwater, S. (2007). Bayesian inference for PCFGs via Markov chain Monte Carlo. Proceedings of the North American Conference on Computational Linguistics (NAACL'07). (pdf) |
| Kirby, S., Dowman, M., & Griffiths, T. (2007). Innateness and culture in the evolution of language. Proceedings of the National Academy of Sciences, 104, 5241-5245. (pdf) |
| 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) |
| Steyvers, M., & Griffiths, T. (2007). Probabilistic topic models. In T. Landauer, D. S. McNamara, S. Dennis, & W. Kintsch (Eds.), Handbook of Latent Semantic Analysis. Hillsdale, NJ: Erlbaum. (pdf) (topic modeling toolbox) |
| Goldwater, S., Griffiths, T. L., & Johnson, M. (2007). Distributional cues to word segmentation: Context is important. Proceedings of the 31st Boston University Conference on Language Development. (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) |
| Griffiths, T. L., & Yuille, A. (2006). A primer on probabilistic inference. Trends in Cognitive Sciences. Supplement to special issue on Probabilistic Models of Cognition (volume 10, issue 7). (pdf) |
| 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) |
| Steyvers, M., Griffiths, T. L., & Dennis, S. (2006). Probabilistic inference in human semantic memory. Trends in Cognitive Science, 10, 327-334. (pdf) (topic modeling toolbox) |
| 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) |
| Goldwater, S., Griffiths, T. L., & Johnson, M. (2006). Contextual dependencies in unsupervised word segmentation. Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics.(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) |
| Bonawitz, E. B., Griffiths, T. L., & Schulz, L. (2006). Modeling cross-domain causal learning in preschoolers as Bayesian inference. Proceedings of the 28th Annual Conference of the Cognitive Science Society. (pdf) (winner of the Marr Prize for best student paper) |
| 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., 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) |
| Wood, F., Griffiths, T. L., & Ghahramani, Z. (2006). A non-parametric Bayesian method for inferring hidden causes. Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI 2006). (pdf) |
| Goldwater, S., Griffiths, T. L., & Johnson, M. (2006). Interpolating between types and tokens by estimating power law generators. Advances in Neural Information Processing Systems 18. (pdf) (note: this version of the paper is slightly modified from the hardcopy proceedings) |
| Griffiths, T. L., & Ghahramani, Z. (2006). Infinite latent feature models and the Indian buffet process. Advances in Neural Information Processing Systems 18. (pdf) |
| Navarro, D. J., Griffiths, T. L., Steyvers, M., & Lee, M. D. (2006). Modeling individual differences using Dirichlet processes. Journal of Mathematical Psychology, 50, 101-122. (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) |
| Griffiths, T. L., & Kalish, M. L. (2005). A Bayesian view of language evolution by iterated learning. Proceedings of the 27th Annual Conference of the Cognitive Science Society. (pdf) |
| Navarro, D.J., Griffiths, T. L., Steyvers, M., & Lee, M. D. (2005). Modeling individual differences with Dirichlet processes. Proceedings of the 27th Annual Conference of the Cognitive Science Society. (pdf) |
| Griffiths, T. L., & Ghahramani, Z. (2005). Infinite latent feature models and the Indian buffet process. Gatsby Computational Neuroscience Unit Technical Report GCNU TR 2005-001. (pdf) |
| 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) |
| Griffiths, T. L. (2005). Causes, coincidences, and theories. Unpublished doctoral dissertation, Stanford University, Stanford CA. (pdf) |
| Kemp, C., Griffiths, T. L., & Tenenbaum, J. B. (2004). Discovering latent classes in relational data. AI Memo 2004-019 (pdf) |
| Steyvers, M., Smyth, P., Rosen-Zvi, M., & Griffiths, T. (2004). Probabilistic Author-Topic models for information discovery. The Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (pdf) (demo) (topic modeling toolbox) |
| Rosen-Zvi, M., Griffiths, T., Steyvers, M., & Smyth, P. (2004). The Author-Topic Model for authors and documents. 20th Conference on Uncertainty in Artificial Intelligence. (pdf) (demo) (topic modeling toolbox) |
| Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101, 5228-5235. (pdf) (topic modeling toolbox) |
| 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., & Steyvers, M. (2003). Prediction and semantic association. Advances in Neural Information Processing Systems 15. (pdf) (topic modeling toolbox) |
| 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., & Kalish, M. L. (2002). A multidimensional scaling approach to mental multiplication. Memory and Cognition, 30, 97-106. (pdf) |
| Griffiths, T. L., & Tenenbaum, J. B. (2002). Using vocabulary knowledge in Bayesian multinomial estimation. Advances in Neural Information Processing Systems 14. (pdf) |
| Griffiths, T. L., & Steyvers, M. (2002). A probabilistic approach to semantic representation. Proceedings of the 24th Annual Conference of the Cognitive Science Society. (pdf) (topic modeling toolbox) |
| 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) |
| 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) |