The Challenges of Large‐Scale, Web‐Based Language Datasets: Word Length and Predictability Revisited by Meylan, Stephan C., Griffiths, Thomas L.

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Predicting the Future as Bayesian Inference: People Combine Prior Knowledge With Observations When Estimating Duration and Extent by Griffiths, Thomas L., Tenenbaum, Joshua B.

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Intuitive Theories as Grammars for Causal Inference by Tenenbaum, Joshua B., Griffiths, Thomas L., Niyogi, Sourabh

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Discovering Latent Classes in Relational Data by Kemp, Charles, Griffiths, Thomas L., Tenenbaum, Joshua B.

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One and Done? Optimal Decisions From Very Few Samples by Vul, Edward, Goodman, Noah, Griffiths, Thomas L., Tenenbaum, Joshua B.

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A tutorial introduction to Bayesian models of cognitive development by Perfors, Amy, Tenenbaum, Joshua B., Griffiths, Thomas L., Xu, Fei

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Modeling human performance in statistical word segmentation by Frank, Michael C., Goldwater, Sharon, Griffiths, Thomas L., Tenenbaum, Joshua B.

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Compositionality in rational analysis: Grammar-based induction for concept learning by Goodman, Noah D., Tenenbaum, Joshua B., Griffiths, Thomas L., Feldman, Jacob

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Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults by Griffiths, Thomas L., Sobel, David M., Tenenbaum, Joshua B., Gopnik, Alison

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Bayesian collective learning emerges from heuristic social learning by Krafft, P.M., Shmueli, Erez, Griffiths, Thomas L., Tenenbaum, Joshua B., Pentland, Alex

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Preference-Conditioned Language-Guided Abstraction by Peng, Andi, Bobu, Andreea, Li, Belinda Z., Sumers, Theodore R., Sucholutsky, Ilia, Kumar, Nishanth, Griffiths, Thomas L., Shah, Julie A.

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Developmental and computational perspectives on infant social cognition by Hamlin, Kiley, Wynn, Karen, Bloom, Paul, Lucas, Chris G., Griffiths, Thomas L., Xu, Fei, Fawcett, Christine, Tamar, Kushnir, Wellman, Henry, Gelman, Susan, Goodman, Noah Daniel, Baker, Christopher Lawrence, Ullman, Tomer David, Tenenbaum, Joshua B

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