Publications

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F Foundations
P Perception
E Education
CI Causal Induction
CD Cognitive Development
PR Probabilistic Reasoning
RPM Rational Process Models
S&C Similarity and Categorization
SML Statistical Models of Language
NBM Nonparametric Bayesian Models
CEIL Cultural Evolution and Iterated Learning
DRLM Decision Making and Reinforcement Learning

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By Griffiths, T
PR
NBM
Battleday, R. M., & Griffiths, T. L. (preprint). Analogy as Nonparametric Bayesian Inference over Relational Systems. (link)
PR
DRLM
Hardy, M., & Griffiths, T. L. (preprint). Demonstrating the impact of prior knowledge in risky choice. (link)
RPM
DRLM
Callaway, F., & Griffiths, T. L. (preprint). Attention in value-based choice as optimal sequential sampling. (link)
RPM
DRLM
Reichman, D., Lieder, F., Bourgin, D. D., Talmon, N., & Griffiths, T. L. (preprint). Goal pursuit for computationally bounded agents: The network structure of goal systems predicts human performance.
RPM
DRLM
Milli, S., Lieder, F., & Griffiths, T. L. (preprint). A rational reinterpretation of dual process theories. (link)
SML
Meylan, S. C., & Griffiths, T. L. (preprint). Word forms - not just their lengths - are optimized for efficient communication. (link)
S&C
Battleday, R. M., Peterson, J. C., & Griffiths, T. L. (in press). Modeling human categorization of natural images using deep feature representations. Nature Communications. (pdf)
F
Alon, N., Cohen, J. D., Griffiths, T. L., Manurangsi, P., Reichman, D., Shinkar, I., Wagner, T., Yu, A. (in press). Multitasking capacity: Hardness results and improved constructions. SIAM Journal on Discrete Mathematics. (pdf)
E
Rafferty, A. N, Jansen, R. A., Griffiths, T. L. (2020). Assessing mathematics misunderstandings via Bayesian inverse planning. Cognitive Science. (pdf)
RPM
Lieder, F., & Griffiths, T. L. (2020). Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences, 43, e1. (pdf)
S&C
SML
Peterson, J., Chen, D., & Griffiths, T. (2020). Parallelograms revisited: Exploring the limitations of vector space models for simple analogies. Cognition, 205, 104440. (pdf)
E
DRLM
Dubey, R., & Griffiths, T. L. (2020). Reconciling novelty and complexity through a rational analysis of curiosity. Psychological Review, 127(3), 455-476. (pdf)
CEIL
Morgan, T. J. H., Suchow, J. W., & Griffiths, T. L. (2020). Experimental evolutionary simulations of learning, memory and life history. Philosophical Transactions of the Royal Society B, 375, 20190504. (pdf)
F
DRLM
Gates, V., Griffiths, T. L., & Dragan, A. D. (2020). How to be helpful to multiple people at once. Cognitive Science, 44(6), e12841. (pdf)
CEIL
Morgan, T. J. H., Suchow, J. W., & Griffiths, T. L. (2020). What the Baldwin Effect affects depends on the nature of plasticity. Cognition, 197, 104165. (pdf)
RPM
DRLM
Correa, C. G.*, Ho, M. K.*, Callaway, F., & Griffiths, T. L. (2020). Resource-rational Task Decomposition to Minimize Planning Costs. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
SML
McCoy, R. T., Grant, E., Smolensky, P., Griffiths, T. L., & Linzen, T. (2020). Universal linguistic inductive biases via meta-learning. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
E
PR
Jansen, R. A., Rafferty, A. N., & Griffiths, T. L. (2020). A rational model of sequential self-assessment. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
P
S&C
Jha, A., Peterson, J., & Griffiths, T. L. (2020). Extracting low-dimensional psychological representations from convolutional neural networks. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
SML
CEIL
Hawkins, R. D., Goodman, N. D., Goldberg, A. E., & Griffiths, T. L. (2020). Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
P
DRLM
Sumers, T. R., Ho, M. K., & Griffiths, T. L. (2020). Show or tell? Demonstration is more robust to changes in shared perception than explanation. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
P
S&C
Singh, P., Peterson, J. C., Battleday, R. M., & Griffiths, T. L. (2020). End-to-end deep prototype and exemplar models for predicting human behavior. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
DRLM
Ho, M. K., Abel, D., Cohen, J. D., Littman, M. L., & Griffiths, T. L. (2020). The Efficiency of Human Cognition Reflects Planned Information Processing. Proceedings of the 34th AAAI Conference on Artificial Intelligence. (pdf)
RPM
DRLM
Agrawal, M., Peterson, J. C., & Griffiths, T. L. (2020). Scaling up psychology via Scientific Regret Minimization. Proceedings of the National Academy of Sciences. (pdf)
PR
NBM
Jerfel, G., Grant, E. L., Griffiths, T. L., & Heller, K. (2019). Reconciling meta-learning and continual learning with online mixtures of tasks. Advances in Neural Information Processing Systems. (pdf)
E
Jupyter, P., Blank, D., Bourgin, D., Brown, A., Bussonnier, M., Frederic, J., Granger, B., Griffiths, T. L., Hamrick, J., Kelley, K., Pacer, M., Page, L., Perez, F., Ragan-Kelley, B., Suchow, J. W., & Willing, C. (2019). nbgrader: A tool for creating and grading assignments in the Jupyter notebook. Journal of Open Source Education, 2(11), 32. (pdf)
DRLM
Lieder, F., Chen, O. X., Krueger, P. M., & Griffiths, T. L. (2019). Cognitive prostheses for goal achievement. Nature Human Behaviour, 3(10), 1096-1106. (pdf)
S&C
Austerweil, J. L., Sanborn, S., & Griffiths, T. L. (2019). Learning how to generalize. Cognitive Science, 43(8), e12777. (pdf)
F
DRLM
Ho, M. K., Abel, D., Griffiths, T. L., & Littman, M. L. (2019). The value of abstraction. Current Opinion in Behavioral Sciences, 29, 111-116. (pdf)
F
RPM
Griffiths, T. L., Callaway, F., Chang, M. B., Grant, E., Krueger, P. M., & Leider, F. (2019). Doing more with less: meta-reasoning and meta-learning in humans and machines. Current Opinion in Behavioral Sciences, 29, 24-30. (pdf)
PR
S&C
Hsu, A. S., Martin, J. B., Sanborn, A. N., & Griffiths, T. L. (2019). Identifying category representations for complex stimuli using discrete Markov chain Monte Carlo with people. Behavior Research Methods, 51, 1706-1716. (pdf)
DRLM
Carroll, M., Shah, R., Ho, M. K., Griffiths, T., Seshia, S., Abbeel, P., & Dragan, A. (2019). On the Utility of Learning about Humans for Human-AI Coordination. In H. Wallach, H. Larochelle, A. Beygelzimer, F. Alché-Buc, E. Fox, & R. Garnett (Eds.), Advances in Neural Information Processing Systems, 32, 5174–5185. (pdf)
P
S&C
Grant, E., Peterson, J., & Griffiths, T. (2019). Learning deep taxonomic priors for concept learning from few positive examples. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pdf)
P
S&C
Peterson, J., Battleday, R., Griffiths, T. L., & Russakovsky, O. (2019). Human uncertainty makes classification more robust. Proceedings of the IEEE International Conference on Computer Vision. (pdf)
E
Dubey, R., Griffiths, T. L., & Lombrozo, T. (2019). If it’s important, then I am curious: A value intervention to induce curiosity. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pdf)
RPM
DRLM
Chang, M. B., Gupta, A., Levine, S., & Griffiths, T. L. (2019). Automatically composing representation transformations as a means for generalization. Proceedings of the 7th International Conference on Learning Representations (ICLR) 2019. (pdf)
CEIL
Thompson, B., & Griffiths, T. L. (2019). Inductive biases constrain cumulative cultural evolution. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pdf)
PR
DRLM
Ho, M. K., Korman, J., & Griffiths, T. L. (2019). The computational structure of unintentional meaning. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pdf)
DRLM
Bourgin, D., Peterson, J., Reichman, D., Russell, S., & Griffiths, T. L. (2019). Cognitive model priors for predicting human decisions. Proceedings of the 36th International Conference on Machine Learning (ICML). (pdf)
RPM
DRLM
Agrawal, M., Peterson, J.C., & Griffiths, T. L. (2019). Using machine learning to guide cognitive modeling: a case study in moral reasoning. Proceedings of the 41st Annual Conference of the Cognitive Science Society . (pdf)
PR
Griffiths, T. L., Daniels, D., Austerweil, J. L., & Tenenbaum, J. B. (2018). Subjective randomness as statistical inference. Cognitive Psychology, 103, 85-109. (pdf)
P
S&C
Peterson, J. C., Abbott, J. T., & Griffiths, T. L. (2018). Evaluating (and improving) the correspondence between deep neural networks and human representations. Cognitive Science, 42, 2648-2669. (pdf)
RPM
DRLM
Lieder, F., Shenhav, A., Musslick, S., & Griffiths, T.L. (2018). Rational metareasoning and the plasticity of cognitive control. PLoS Computational Biology, 14, e1006043. (pdf)
PR
RPM
DRLM
Lieder, F., Griffiths, T. L., Huys, Q. J. M., & Goodman, N. D. (2018). Empirical evidence for resource-rational anchoring and adjustment. Psychonomic Bulletin & Review, 25, 775-784. (pdf)
PR
RPM
DRLM
Lieder, F., Griffiths, T. L., Huys, Q. J. M., & Goodman, N. D. (2018). The anchoring bias reflects rational use of cognitive resources. Psychonomic Bulletin & Review, 25, 322-349. (pdf)
PR
RPM
DRLM
Lieder, F., Griffiths, T. L., & Hsu, M (2018). Over-representation of extreme events in decision making reflects rational use of cognitive resources. Psychological Review, 125(1), 1-32. (pdf)
CEIL
Whalen, A., Griffiths, T. L., & Buchsbaum, D. (2018). Sensitivity to shared information in social learning. Cognitive Science, 42(1), 168-187. (pdf)
RPM
DRLM
Callaway, F., Gul, S., Krueger, P. M., Griffiths, T. L., & Lieder, F. (2018). Learning to select computations. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence. (pdf)
DRLM
Burns, K., Nematzadeh, A., Grant, E., Gopnik, A., & Griffiths, T. L. (2018). Exploiting attention to reveal shortcomings in memory models. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 378-380. (pdf)
DRLM
Dubey, R., Agrawal, P., Pathak, D., Griffiths, T. L., & Efros, A. A. (2018). Investigating human priors for playing video games. In Proceedings of the 35th International Conference on Machine Learning (ICML 2018). (pdf) (project website)
SML
Nematzadeh, A., Burns, K., Grant, E., Gopnik, A., & Griffiths, T. L. (2018). Evaluating theory of mind in question answering. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. (pdf)
PR
Grant, E., Finn, C., Levine, S., Darrell, T., & Griffiths, T. L. (2018). Recasting gradient-based meta-learning as hierarchical Bayes. In Proceedings of the 6th International Conference on Learning Representations (ICLR). (pdf)
P
S&C
Suchow, J. W., Peterson, J. C., & Griffiths, T. L. (2018). Learning a face space for experiments on human identity. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
DRLM
Krueger, P. M., & Griffiths, T. L. (2018). Shaping model-free habits with model-based goals. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
S&C
Bourgin, D. D., Abbott, J. T., & Griffiths, T. L. (2018). Recommendation as generalization: Evaluating cognitive models in the wild. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
F
CEIL
Krafft, P. M., & Griffiths, T. L. (2018). Levels of analysis in computational social science. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
DRLM
Sanborn, S., Bourgin, D. D., Chang, M., & Griffiths, T. L. (2018). Representational efficiency outweighs action efficiency in human program induction. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
S&C
Peterson, J. C., Suchow, J. W., Aghi, K., Ku, A. Y., & Griffiths, T. L. (2018). Capturing human category representations by sampling in deep feature spaces. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
S&C
SML
Peterson, J. C., Soulos, P., Nematzadeh, A., & Griffiths, T. L. (2018). Learning hierarchical visual representations in deep neural networks using hierarchical linguistic labels. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
E
Jansen, R. A., Rafferty, A. N., & Griffiths, T. L. (2018). Modeling the Dunning-Kruger Effect: A rational account of inaccurate self assessment. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
RPM
DRLM
Callaway, F., Lieder, F., Das, P., Gul, S., Krueger, P. M., & Griffiths, T. L. (2018). A resource-rational analysis of human planning. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
F
Alon, N., Reichman, D., Shinkar, I., Wagner, T., Musslick, S., Cohen, J. D., Griffiths, T. L., Dey, B., & Ozcimder, K. (2017). A graph-theoretic approach to multitasking. Advances in Neural Information Processing Systems, 2100-2109. (pdf)
SML
de Heer, W. A., Huth, A. G., Griffiths, T. L., Gallant, J. L., & Theunissen, F. E. (2017). The hierarchical cortical organization of human speech processing. Journal of Neuroscience, 37(27), 6539-6557. (pdf)
PR
RPM
DRLM
Lieder, F., & Griffiths, T. L. (2017). Strategy selection as rational metareasoning. Psychological Review, 124(6), 762-794. (pdf)
F
Paxton, A., & Griffiths, T. L.(2017). Finding the traces of behavioral and cognitive processes in big data and naturally occurring datasets. Behavior Research Methods, 49(5), 1630-1638.(pdf)
F
CEIL
Suchow, J. W., Bourgin, D. D., & Griffiths, T. L. (2017). Evolution in mind: Evolutionary dynamics, cognitive processes, and Bayesian inference. Trends in Cognitive Sciences, 21(7), 522-530. (pdf)
CI
Griffiths, T. L. (2017). Formalizing prior knowledge in causal induction. The Oxford Handbook of Causal Reasoning. Oxford: Oxford University Press. (book)
CI
RPM
Bramley, N. R., Dayan, P., Griffiths, T. L., & Lagnado, D. A. (2017). Formalizing Neuraths Ship: Approximate algorithms for online causal learning. Psychological Review, 124(3), 301-338. (pdf)
P
Austerweil, J. L., Griffiths, T. L., & Palmer, S. E. (2017). Learning to be (in) variant: Combining prior knowledge and experience to infer orientation invariance in object recognition. Cognitive Science, 41(S5), 1183-1201. (pdf)
RPM
Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M. (2017). Toward a rational and mechanistic account of mental effort. Annual Review of Neuroscience.(pdf)
SML
CEIL
Whalen, A., & Griffiths, T. L. (2017). Adding population structure to models of language evolution by iterated learning. Journal of Mathematical Psychology, 76, 1-6. (pdf)
PR
DRLM
Fisac, J. F., Gates, M. A., Hamrick, J. B., Liu, C., Hadfield-Menell, D., Palaniappan, M., Malik, D., Sastry, S. S., Griffiths, T. L., & Dragan, A. D. (2017). Pragmatic-Pedagogic Value Alignment. International Symposium on Robotics Research. (pdf)
CD
Gopnik, A., O'Grady, S., Lucas, C. G., Griffiths, T. L., Wente, A., Bridgers, S., Aboody, R., Fung, H., & Dahl, R. E. (2017). Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood. Proceedings of the National Academy of Sciences, 114(30), 7892-7899. (pdf)
PR
Meng, Y., Griffiths, T. L., & Xu, F. (2017). Inferring intentional agents from violation of randomness. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
P
CEIL
Langlois, T. A., Jacoby, N., Suchow, J. W., & Griffiths, T. L. (2017). Uncovering visual priors in spatial memory using serial reproduction. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
RPM
Bourgin, D. D., Lieder, F., Reichman, D., Talmon, N., & Griffiths, T. L. (2017). The structure of goal systems predicts human performance. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
E
PR
Dubey, R., & Griffiths, T. L. (2017). A rational analysis of curiosity. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
CD
SML
Grant, E., Nematzadeh, A., & Griffiths, T. L. (2017). How can memory-augmented neural networks pass a false-belief task? Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
SML
Nematzadeh, A., Meylan, S. C., & Griffiths, T. L. (2017). Evaluating vector-space models of word representation, or the unreasonable effectiveness of counting words near other words. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
E
Jansen, R. A., Rafferty, A. N., & Griffiths, T. L. (2017). Algebra is not like trivia: Evaluating self-assessment in an online math tutor. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
DRLM
Krueger, P. M., Lieder, F., & Griffiths, T. L. (2017). Enhancing metacognitive reinforcement learning using reward structures and feedback. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
RPM
DRLM
Lieder, F., Krueger, P. M., & Griffiths, T. L. (2017). An automatic method for discovering rational heuristics for risky choice. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
P
CI
Callaway, F., Hamrick, J. B., & Griffiths, T. L. (2017). Discovering simple heuristics from mental simulation. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
S&C
SML
Chen, D., Peterson, J. C., & Griffiths, T. L. (2017). Evaluating vector-space models of analogy. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
CEIL
Gates, M. A., Suchow, J. W., & Griffiths, T. L. (2017). Empirical tests of large-scale collaborative recall. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
P
S&C
Peterson, J. C., & Griffiths, T. L. (2017). Evidence for the size principle in semantic and perceptual domains. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Milli, S., Lieder, F., & Griffiths, T. L. (2017) When does bounded-optimal metareasoning favor few cognitive systems? Proceedings of the 31st AAAI Conference on Artificial Intelligence. (pdf)
SML
Huth, A. G., de Heer, W. A., Griffiths, T. L., Theunissen, F. E., & Gallant, J. L. (2016). Natural speech reveals the semantic maps that tile the human cerebral cortex. Nature, 532 453-458. (pdf)
P
CI
PR
Hamrick, J. B., Battaglia, P. W., Griffiths, T. L., Tenenbaum, J. B. (2016). Inferring mass in complex scenes by mental simulation. Cognition, 157, 61-76. (pdf)
CD
PR
Ruggeri, A., Lombrozo, T., Griffiths, T. L., & Xu, F. (2016). Sources of developmental change in the efficiency of information search. Developmental Psychology, 52, 2159-2173. (pdf)
PR
SML
Hsu, A., & Griffiths, T. L. (2016). Sampling assumptions affect use of indirect negative evidence in language learning PLOS One, 11(6). (pdf)
F
P
Griffiths, T. L., Abbott, J. T., & Hsu, A. S. (2016). Exploring human cognition using large image databases. Topics in Cognitive Science, 8(3), 569-588. (pdf)
SML
Cibelli, E., Xu, Y., Austerweil, J. L., Griffiths, T. L., & Regier, T. (2016). The Sapir-Whorf Hypothesis and probabilistic inference: Evidence from the domain of color. PLOS One, 11(7). (pdf)
CD
PR
Eaves Jr, B. S., Feldman, N. H., Griffiths, T. L., & Shafto, P. (2016). Infant-directed speech is consistent with teaching. Psychological Review (pdf)
RPM
Hsu, A. S., Horng, A., Griffiths, T. L., & Chater, N. (2016). When absence of evidence is evidence of absence: Rational inferences from absent data. Cognitive Science, 1-13. (pdf)
CI
CD
Bridgers, S., Buchsbaum, D., Seiver, E., Griffiths, T. L., & Gopnik, A. (2016). Children's causal inferences from conflicting testimony and observations. Developmental Psychology. (pdf)
PR
Fisac, J. F., Liu, C., Hamrick, J. B., Sastry, S., Hedrick, J. K., Griffiths, T. L., & Dragan, A. D. (2016). Generating plans that predict themselves. In Proceedings of the 12th International Workshop on the Algorithmic Foundations of Robotics (WAFR 2016). (pdf)
F
CEIL
Suchow, J. W., & Griffiths, T. L. (2016). Rethinking experiment design as algorithm design. CrowdML – NIPS '16 Workshop on Crowdsourcing and Machine Learning. (pdf)
RPM
Lieder, F., & Griffiths, T. L. (2016). Helping people make better decisions using optimal gamification Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
E
Rafferty, A. N., Jansen, R. A, & Griffiths, T. L. (2016). Using inverse planning for personalized feedback. Proceedings of the 9th International Conference on Educational Data Mining, 472-477. (pdf)
P
S&C
Abbott, J. T., Griffiths, T. L., & Regier, T. (2016). Focal colors across languages are representative members of color categories. Proceedings of the National Academy of Sciences, 113(40), 11178-11183. (pdf)
PR
O'Grady, S., Griffiths, T. L., & Xu, F. (2016). Do simple probability judgements rely on integer approximation? Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
CD
Foushee, R., Griffiths, T. L., & Srinivasan, M. (2016). Lexical complexity of child-directed and overheard speech: Implications for learning. Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
P
CEIL
Suchow, J. W., Pacer, M. D., & Griffiths, T. L. (2016). Design from Zeroth Principles. Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Suchow, J. W., & Griffiths, T. L. (2016). Deciding to remember: Memory maintenance as a Markov Decision Process. Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
P
S&C
Peterson, J., Abbott, J. T., & Griffiths, T. L. (2016). Adapting deep network features to capture psychological representations. Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf) (Winner of the Computational Modeling Prize in Perception/Action)
P
PR
Liu, C., Hamrick, J. B., Fisac, J. F., Dragan, A. D, Hendrick, J. K., Sastry, S. S, & Griffiths, T. L. (2016). Goal inference improves objective and perceived performance in human-robot collaboration. Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems. (pdf)
CD
PR
Hu, J., Lucas, C. G., Griffiths, T. L., & Xu, F. (2015). Preschoolers' understanding of graded preferences. Cognitive Development, 36, 93-102. (pdf)
E
S&C
Rafferty, A. N., Brunskill, E., Griffiths, T. L., & Shafto, P. (2015). Faster teaching via POMDP planning. Cognitive Science. (pdf)
F
Sanborn, A. N., & Griffiths, T. L. (2015). Exploring the structure of mental representations by implementing computer algorithms with people. In Raaijmakers, J. G. W., Criss, A. H., Goldstone, R. L., Nosofsky, R. M., & Steyvers, M. (Eds.). Cognitive Modeling in Perception and Memory: A Festschrift for Richard M. Shiffrin. New York: Psychology Press. (pdf)
RPM
SML
Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2015). Random walks on semantic networks can resemble optimal foraging. Psychological Review, 122, 558-569. (pdf)
F
RPM
Griffiths, T. L., Lieder, F., & Goodman, N. D. (2015). Rational use of cognitive resources: Levels of analysis between the computational and the algorithmic. Topics in Cognitive Science, 7, 217-229. (pdf)
PR
Rafferty, A. N., LaMar, M. M., & Griffiths, T. L. (2015). Inferring learners' knowledge from their actions. Cognitive Science, 39, 584-618. (pdf)
F
Goodman, N. D., Frank, M. C., Griffiths, T. L., Tenenbaum, J. B., Battaglia, P., & Hamrick, J. B. (2015). Relevant and robust. A response to Marcus and Davis. Psychological Science, 26, 539-541. (pdf)
F
Griffiths, T. L. (2015). Manifesto for a new (computational) cognitive revolution. Cognition, 135, 21-23. (pdf)
CD
RPM
Gopnik, A., Griffiths, T. L., & Lucas, C. G. (2015). When younger learners can be better (or at least more open-minded) than older ones. Current Directions in Psychological Science, 24, 87-92. (pdf)
CI
NBM
Lucas, C. G., Griffiths, T. L., Williams, J. J., & Kalish, M. L. (2015). A rational model of function learning. Psychonomic Bulletin and Review. (pdf)
CI
CEIL
Yeung, S., & Griffiths, T. L. (2015). Identifying expectations about the strength of causal relationships. Cognitive Psychology, 76, 1-29. (pdf)
CI
SML
NBM
Buchsbaum, D., Griffiths, T. L., Plunkett, D., Gopnik, A., & Baldwin, D. (2015). Inferring action structure and causal relationships in continuous sequences of human action. Cognitive Psychology, 76, 30-77. (pdf)
PR
S&C
Griffiths, T. L. (2015). Revealing ontological commitments by magic. Cognition, 136, 43-48. (pdf)
E
Rafferty, A. N., & Griffiths, T. L. (2015). Interpreting freeform equation solving. Proceedings of the 17th International Conference on Artificial Intelligence in Education. (pdf)
P
RPM
Hamrick, J., Smith, K. A., Griffiths, T. L., & Vul, E. (2015). Think again? The amount of mental simulation tracks uncertainty in the outcome. Proceedings of the 37th Annual Conference of the Cognitive Science Society (pdf)
CD
Hu, J., Whalen, A., Buchsbaum, D., Griffiths, T. L., & Xu, F. (2015). Can children balance the size of a majority with the quality of their information? Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Lieder, F., & Griffiths, T. L. (2015). When to use which heuristic: A rational solution to the strategy selection problem. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
CD
PR
Lieder, F., Sim, Z., Hu, J. C., & Griffiths, T. L. (2015). Children and adults differ in their strategies for social learning. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
CD
SML
Meylan, S. C., & Griffiths, T. L. (2015). A Bayesian framework for learning words from multiword utterances. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
CEIL
Morgan, T. J. H, & Griffiths, T. L. (2015). What the Baldwin Effect affects. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
CI
Pacer, M. D., & Griffiths, T. L. (2015). Upsetting the contingency table: Causal induction over sequences of point events. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
CI
CD
Ruggeri, A., Lombrozo, T., Griffiths, T. L., & Xu, F. (2015). Children search for information as efficiently as adults, but seek additional confirmatory evidence. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
RPM
Lieder, F., Plunkett, D., Hamrick, J. B., Russell, S. J., Hay, N. J., & Griffiths, T. L. (2014). Algorithm selection by rational metareasoning as a model of human strategy selection. Advances in Neural Information Processing Systems, 27. (pdf)
SML
CEIL
Rafferty, A. N., Griffiths, T. L., & Klein, D. (2014). Analyzing the rate at which languages lose the influence of a common ancestor. Cognitive Science, 38, 1406-1431. (pdf)
CI
CD
PR
Bonawitz, E., Denison, S., Griffiths, T. L., & Gopnik, A. (2014). Probabilistic models, learning algorithms, and response variability: Sampling in cognitive development. Trends in Cognitive Sciences, 18, 497-500. (pdf)
CEIL
Kirby, S., Griffiths, T. L., & Smith, K. (2014). Iterated learning and the evolution of language. Current Opinion in Neurobiology, 28, 108-114. (pdf)
CI
RPM
Bonawitz, E., Denison, S., Gopnik, A., & Griffiths, T. L. (2014). Win-stay, lose-sample,: A simple sequential algorithm for approximating Bayesian inference. Cognitive Psychology, 74, 35-65. (pdf)
PR
RPM
Vul, E., Goodman, N. D., Tenenbaum, J. B., & Griffiths, T. L. (2014). One and done? Optimal decisions from very few samples. Cognitive Science, 38, 599-637. (pdf)
S&C
CEIL
Canini, K. R., Griffiths, T. L., Vanpaemel, W., & Kalish, M. L. (2014). Revealing human inductive biases for category learning by simulating cultural transmission. Psychonomic Bulletin & Review, 21, 785-793. (pdf)
CI
CD
Lucas, C. G., Bridgers, S., Griffiths, T. L., & Gopnik, A. (2014). When children are better (or at least more open-minded) learners than adults: Developmental differences in learning the forms of causal relationships. Cognition, 131, 284-299. (pdf)
CD
PR
Lucas, C. G., Griffiths, T. L., Xu, F., Fawcett, C., Gopnik, A., Kushnir, T., Markson, L., & Hu, J. (2014). The child as econometrician: A rational model of preference understanding in children. PLOS One, 9(3), e92160. (pdf)
PR
S&C
Shafto, P., Goodman, N. D., & Griffiths, T. L. (2014). A rational account of pedagogical reasoning: Teaching by, and learning from, examples. Cognitive Psychology, 71, 55-89. (pdf)
S&C
Rafferty, A. N., Zaharia, M., & Griffiths, T. L. (2014). Optimally designing games for behavioural research. Proceedings of the Royal Society Series A, 470. (pdf)
SML
CEIL
Maurits, L., & Griffiths, T. L. (2014). Tracing the roots of syntax with Bayesian phylogenetics. Proceedings of the National Academy of Sciences, 111, 13576-13581. (pdf)
PR
Bertolero, M. A., & Griffiths, T. L. (2014). Is holism a problem for inductive inference? A computational analysis. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
RPM
SML
Bourgin, D. D., Abbott, J. T., Griffiths, T. L., Smith, K. A., & Vul, E. (2014). Empirical evidence for Markov chain Monte Carlo in memory search. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Hamrick, J. B., & Griffiths, T. L. (2014). What to simulate? Inferring the right direction for mental rotation. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Lieder, F., Hsu, M., & Griffiths, T. L. (2014). The high availability of extreme events serves resource-rational decision-making. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
RPM
Neumann, R., Rafferty, A. N., & Griffiths, T. L. (2014). A bounded rationality account of wishful thinking. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
RPM
Press, A., Pacer, M., Griffiths, T. L., & Christian, B. (2014). Caching algorithms and rational models of memory. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
S&C
CEIL
Whalen, A., Maurits, L., Pacer, M., & Griffiths, T. L. (2014). Cultural evolution with sparse testimony: When does the cultural ratchet slip? Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
SML
NBM
Feldman, N. H., Griffiths, T. L., Goldwater, S., & Morgan, J. (2013). A role for the developing lexicon in phonetic category acquisition. Psychological Review, 120, 751-778. (pdf)
SML
CEIL
Rafferty, A. N., Griffiths, T. L., & Ettlinger, M. (2013). Greater learnability is not sufficient to produce cultural universals. Cognition, 129, 70-87. (pdf)
PR
Williams, J. J., & Griffiths, T. L. (2013). Why are people bad at detecting randomness? A statistical argument. Journal of Experimental Psychology: Learning, Memory & Cognition, 39, 1473-1490. (pdf)
P
S&C
Jia, Y., Abbott, J. T., Austerweil, J. L., Griffiths, T. L., & Darrell, T. (2013). Visual concept learning: Combining machine vision and Bayesian generalization on concept hierarchies. Advances in Neural Information Processing Systems, 26. (pdf)
S&C
NBM
Austerweil, J., & Griffiths, T. L. (2013). A nonparametric Bayesian framework for constructing flexible feature representations. Psychological Review, 120, 817-851. (pdf)
S&C
SML
Feldman, N. H., Myers, E. B., White, K. S., Griffiths, T. L., & Morgan, J. L. (2013). Word-level information influences phonetic learning in adults and infants. Cognition, 127, 427-438. (pdf)
P
CI
Sanborn, A. N., Mansinghka, V. K., & Griffiths, T. L. (2013). Reconciling intuitive physics and Newtonian mechanics for colliding objects. Psychological Review, 120, 411-437. (pdf)
PR
Schlerf, J., Xu, J., Klemfuss, N., Griffiths, T. L., & Ivry, R. B. (2013). Individuals with cerebellar degeneration show similar adaptation deficits with large and small visuomotor errors. Journal of Neurophysiology, 109, 1164-1173. (pdf)
CEIL
Griffiths, T. L., Lewandowsky, S., & Kalish, M. L. (2013). The effects of cultural transmission are modulated by the amount of information transmitted. Cognitive Science, 37, 953-967. (pdf)
CI
RPM
Denison, S., Bonawitz, E., Gopnik, A., & Griffiths, T. L. (2013). Rational variability in children's causal inferences: The Sampling Hypothesis. Cognition, 126, 285-300. (pdf)
PR
RPM
Abbott, J. T., Hamrick, J. B., & Griffiths, T. L. (2013). Approximating Bayesian inference with a sparse distributed memory system. Proceedings of the 35th Annual Conference of the Cognitive Science Society. (pdf)
CI
CEIL
Hu, J.. C, Buchsbaum, D., Griffiths, T. L., & Xu, F. (2013). 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)
PR
CEIL
Whalen, A., Buchsbaum, D., & Griffiths, T. L. (2013). How do you know that? Sensitivity to statistical dependency in social learning. Proceedings of the 35th Annual Conference of the Cognitive Science Society. (pdf)
CI
PR
Pacer, M., Williams, J., Xi, C., Lombrozo, T., & Griffiths, T. L. (2013). Evaluating computational models of explanation using human judgments. Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence. (pdf)
S&C
CEIL
Xu, J., Dowman, M., & Griffiths, T. L. (2013) Cultural transmission results in convergence towards colour term universals. Proceedings of the Royal Society, Series B. (pdf)
SML
CEIL
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. (pdf)
RPM
SML
Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2012). Human memory search as a random walk in a semantic network. Advances in Neural Information Processing Systems, 25. (pdf)
S&C
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)
P
S&C
Austerweil, J. L., & Griffiths, T. L. (2012). Human feature learning. Encyclopedia of the sciences of learning. N. M. Seel, ed. New York: Springer. (book)
PR
RPM
Lieder, F., Griffiths, T. L., & Goodman, N. D. (2012). Burn-in, bias, and the rationality of anchoring. Advances in Neural Information Processing Systems, 25. (pdf)
CEIL
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)
CD
RPM
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)
F
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)
F
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. (pdf)
S&C
Griffiths, T. L., & Austerweil, J. L. (2012). Bayesian generalization with circular consequential regions. Journal of Mathematical Psychology, 56, 281-285. (pdf)
F
RPM
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. (pdf)
CI
CD
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)
S&C
CEIL
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)
S&C
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)
S&C
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)
PR
S&C
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)
F
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)
P
S&C
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)
P
S&C
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)
CI
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)
PR
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)
CI
CD
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)
P
NBM
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)
PR
S&C
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)
CI
Pacer, M., & Griffiths, T. L. (2011). A rational model of causal induction with continuous causes. Advances in Neural Information Processing Systems, 24. (pdf)
P
NBM
Austerweil, J. L., & Griffiths, T. L. (2011). A rational model of the effects of distributional information on feature learning. Cognitive Psychology, 63, 173-209. (pdf)
SML
NBM
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)
F
CD
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)
CI
CD
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)
PR
Austerweil, J. L., & Griffiths, T. L. (2011). Seeking confirmation is rational for deterministic hypotheses. Cognitive Science, 35, 499-526. (pdf)
NBM
Griffiths, T. L., & Ghahramani, Z. (2011). The Indian Buffet Process: An introduction and review. Journal of Machine Learning Research, 12, 1185-1224. (pdf)
S&C
NBM
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. W.ills (Eds.) Formal approaches in categorization. Cambridge, UK: Cambridge University Press. (book)
F
CD
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. (pdf)
SML
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)
SML
Griffiths, T. L. (2011). Rethinking language: How probabilities shape the words we use. Proceedings of the National Academy of Sciences, 108, 3825-3826. (pdf)
SML
CEIL
Griffiths, T. L., & Reali, F. (2011). Modelling minds as well as populations. Proceedings of the Royal Society, Series B. (pdf)
E
PR
S&C
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)
S&C
NBM
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)
CI
CEIL
Yeung, S., & Griffiths, T. L. (2011). Estimating human priors on causal strength. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (pdf)
S&C
CEIL
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)
CI
RPM
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)
PR
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)
P
SML
Buchsbaum, D., Canini, K. R., & 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)
SML
CEIL
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)
CI
RPM
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)
SML
NBM
Frank, M., Goldwater, S., Griffiths, T. L., & Tenenbaum, J. B. (2010). Modeling human performance in statistical word segmentation. Cognition, 117, 107-125.(pdf)
RPM
S&C
NBM
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)
PR
RPM
S&C
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)
P
S&C
NBM
Austerweil, J. L., & Griffiths, T. L. (2010). Learning invariant features using the Transformed Indian Buffet Process. Advances in Neural Information Processing Systems 23. (pdf)
PR
Hsu, A., Griffiths, T. L., & Schreiber, E. (2010). Subjective randomness and natural scene statistics. Psychonomic Bulletin & Review, 17, 624-629. (pdf)
F
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)
SML
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)
F
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.
SML
CEIL
Burkett, D., & Griffiths, T. L. (2010). Iterated learning of multiple languages from multiple teachers. Evolang 8. (pdf)
SML
NBM
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)
CI
NBM
Kemp, C., Tenenbaum, J. B., Niyogi, S., & Griffiths, T. L. (2010). A probabilistic model of theory formation. Cognition, 114, 165-196. (pdf)
CI
Lucas, C. G., & Griffiths, T. L. (2010). Learning the form of causal relationships using hierarchical Bayesian models. Cognitive Science, 34, 113-147. (pdf)
S&C
CEIL
Xu, J., & Griffiths, T. L. (2010). A rational analysis of the effects of memory biases on serial reproduction. Cognitive Psychology, 60, 107-126. (pdf)
PR
RPM
S&C
Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (2010). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, 60, 63-106. (pdf)
SML
CEIL
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. (pdf)
P
S&C
CEIL
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)
S&C
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)
CD
SML
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)
CI
CD
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)
CI
PR
RPM
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)
CI
PR
RPM
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)
P
S&C
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)
CI
CD
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)
S&C
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)
SML
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)
NBM
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)
PR
RPM
Shi, L., & Griffiths, T. L. (2009). Neural implementation of hierarchical Bayesian inference by importance sampling. Advances in Neural Information Processing Systems 22. (pdf)
PR
CEIL
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)
P
S&C
SML
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)
CI
CD
Griffiths, T. L., & Tenenbaum, J. B. (2009). Theory-based causal induction. Psychological Review, 116, 661-716. (pdf)
CEIL
Jaeger, H., Baronchelli, A., Briscoe, T., Christiansen, M. H., Griffiths, T. L., 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.
F
Griffiths, T. L. (2009). Connecting human and machine learning via probabilistic models of cognition. InterSpeech 2009. (pdf)
CD
SML
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian framework for word segmentation: Exploring the effects of context. Cognition, 112, 21-54. (pdf)
SML
CEIL
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)
SML
Canini, K. R., Shi, L., & Griffiths, T. L. (2009). Online inference of topics with Latent Dirichlet Allocation. AISTATS. (pdf)
CD
PR
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)
CI
S&C
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)
RPM
SML
Levy, R., Reali, F., & Griffiths, T. L. (2009). Modeling the effects of memory on human online sentence processing with particle filters. Advances in Neural Information Processing Systems 21. (pdf)
S&C
CEIL
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)
P
S&C
NBM
Austerweil, J., & Griffiths, T. L. (2009). Analyzing human feature learning as nonparametric Bayesian inference. Advances in Neural Information Processing Systems 21. (pdf)
CI
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)
PR
RPM
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)
P
S&C
NBM
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)
CEIL
Beppu, A., & Griffiths, T. L. (2009). Iterated learning and the cultural ratchet. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf)
CI
SML
NBM
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)
SML
NBM
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)
CEIL
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)
SML
CEIL
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)
SML
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)
CEIL
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)
CEIL
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)
S&C
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)
SML
CEIL
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)
S&C
NBM
Navarro, D. J., & Griffiths, T. L. (2008). Latent features in similarity judgment: A nonparametric Bayesian approach. Neural Computation, 20, 2597-2628.(pdf)
S&C
CEIL
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. (pdf)
S&C
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. (pdf)
S&C
NBM
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. (pdf)
S&C
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. (pdf)
SML
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. (pdf)
F
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. (pdf)
F
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. (pdf)
NBM
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)
PR
S&C
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)
SML
CEIL
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)
RPM
S&C
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)
PR
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)
NBM
CEIL
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)
SML
Griffiths, T. L., Steyvers, M., & Firl, A. (2007). Google and the mind: Predicting fluency with PageRank. Psychological Science, 18, 1069-1076. (pdf)
S&C
SML
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)
CI
CD
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)
NBM
Wood, F., & Griffiths, T. L. (2007). Particle filtering for nonparametric Bayesian matrix factorization. Advances in Neural Information Processing Systems 19. (pdf)
SML
NBM
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)
S&C
NBM
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)
CEIL
Griffiths, T. L., & Kalish, M. L. (2007). Language evolution by iterated learning with Bayesian agents. Cognitive Science, 31, 441-480. (pdf)
CEIL
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)
SML
Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007). Topics in semantic representation. Psychological Review, 114,211-244. (pdf) (topic modeling toolbox)
NBM
Ghahramani, Z., Griffiths, T. L., & Sollich, P. (2007). Bayesian nonparametric latent feature models. Bayesian Statistics 8. Oxford University Press. (pdf) (discussion) (rejoinder)
CI
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)
CI
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)
SML
Steyvers, M., & Griffiths, T. L. (2007). Probabilistic topic models. In T. L.andauer, D. S. McNamara, S. Dennis, & W. Kintsch (Eds.), Handbook of Latent Semantic Analysis. Hillsdale, NJ: Erlbaum. (pdf) (topic modeling toolbox)
CI
PR
Griffiths, T. L., & Tenenbaum, J. B. (2007). From mere coincidences to meaningful discoveries. Cognition, 103, 180-226. (pdf)
SML
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)
SML
CEIL
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)
SML
Frank, M. C., Goldwater, S., Mansinghka, V., Griffiths, T., & Tenenbaum, J. B. (2007). Modeling human performance in statistical word segmentation. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (pdf)
S&C
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)
S&C
NBM
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)
S&C
SML
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)
PR
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)
CD
SML
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)
SML
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)
CEIL
Kirby, S., Dowman, M., & Griffiths, T. L. (2007). Innateness and culture in the evolution of language. Proceedings of the National Academy of Sciences, 104, 5241-5245. (pdf)
PR
Griffiths, T. L., & Tenenbaum, J. B. (2006). Optimal predictions in everyday cognition. Psychological Science, 17, 767-773. (pdf) (article in The Economist)
F
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)
F
CI
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)
SML
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)
F
PR
Griffiths, T. L., & Tenenbaum, J. B. (2006). Statistics and the Bayesian mind. Significance, 3, 130-133. (pdf)
CD
SML
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)
NBM
Griffiths, T. L., & Ghahramani, Z. (2006). Infinite latent feature models and the Indian buffet process. Advances in Neural Information Processing Systems 18. (pdf)
NBM
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)
SML
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)
SML
NBM
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)
RPM
S&C
NBM
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)
CI
CD
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)
S&C
CEIL
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)
NBM
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)
CI
NBM
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)
CI
NBM
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)
CI
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)
NBM
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)
SML
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)
SML
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)
CI
Griffiths, T. L. (2005). Causes, coincidences, and theories. Unpublished doctoral dissertation, Stanford University, Stanford CA. (pdf)
CEIL
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)
NBM
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)
S&C
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)
SML
NBM
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)
PR
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)
CI
Kemp, C., Griffiths, T. L., & Tenenbaum, J. B. (2004). Discovering latent classes in relational data. AI Memo 2004-019 (pdf)
CI
CD
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)
SML
Steyvers, M., Smyth, P., Rosen-Zvi, M., & Griffiths, T. L. (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)
SML
Rosen-Zvi, M., Griffiths, T. L., 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)
SML
Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101, 5228-5235. (pdf) (topic modeling toolbox)
CI
Danks, D., Griffiths, T. L., & Tenenbaum, J. B. (2003). Dynamical causal learning. Advances in Neural Information Processing Systems 15. (pdf)
CI
Tenenbaum, J. B., & Griffiths, T. L. (2003). Theory-based causal inference. Advances in Neural Information Processing Systems 15. (pdf)
SML
Griffiths, T. L., & Steyvers, M. (2003). Prediction and semantic association. Advances in Neural Information Processing Systems 15. (pdf) (topic modeling toolbox)
PR
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)
S&C
Griffiths, T. L., & Kalish, M. L. (2002). A multidimensional scaling approach to mental multiplication. Memory and Cognition, 30, 97-106. (pdf)
SML
Griffiths, T. L., & Tenenbaum, J. B. (2002). Using vocabulary knowledge in Bayesian multinomial estimation. Advances in Neural Information Processing Systems, 14. (pdf)
SML
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)
CI
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)
S&C
Tenenbaum, J. B., & Griffiths, T. L. (2001). Generalization, similarity, and Bayesian inference. Behavioral and Brain Sciences, 24,629-641. (pdf)
S&C
Tenenbaum, J. B., & Griffiths, T. L. (2001). Some specifics about generalization. Behavioral and Brain Sciences, 24, 772-778. (html)
PR
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)
PR
Tenenbaum, J. B., & Griffiths, T. L. (2001). The rational basis of representativeness. Proceedings of the 23rd Annual Conference of the Cognitive Science Society. (pdf)
S&C
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)
PR
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)

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