In the works…

Hao, X., Jhaveri, Y., & Shafto, P. (2023). Common ground in cooperative communication. Advances in Neural Information Processing Systems (NeurIPS). (spotlight) pdf

Sheller, B. & Shafto, P. (preprint). The (co)limit of metabeliefs.

Wang, J., Wang, P., & Shafto, P. (2023). Generalized Belief Transport. Advances in Neural Information Processing Systems (NeurIPS). pdf

Yang, S, C-H., Eaves, B., Schmidt, M., Swanson, K., & Shafto, P. (preprint). Structurally informed tabular data synthesis and evaluation.

Li, Z., & Shafto, P. (2023). On feasibility of intent obfuscating attacks. Workshop on New Frontiers in Adversarial Machine Learning (AdvML 2023) at ICML.

Wang, J., Wang, P., & Shafto, P. (2023). Efficient discretizations of Optimal Transport. Entropy. html arXiv

Givchi, A., Wang, P., Wang, J., & Shafto, P. (preprint). Distributionally-Constrained Policy Optimization via Unbalanced Optimal Transport. arXiv

Lu, C-K & Shafto, P. (preprint). On Connecting Deep Trigonometric Networks with Deep Gaussian Processes: Covariance, Expressivity, and Neural Tangent Kernel. arXiv

Sheller, B., Wang, J., & Shafto, P. (preprint). The alignment problem in curriculum learning.

Hao, X. & Shafto, P. (2023). Coupled variational autoencoder. International Conference on Machine Learning (ICML). html arXiv

Barak, L., Harmon, Z., Feldman, N.H., Edwards,J. & Shafto, P. (2023). When children’s production deviates from observed input: Modeling the variable production of the English past tense. Cognitive Science. html

Yang, S., C-H., Folke, T., & Shafto, P. (2023). The inner loop of collective human-machine intelligence. Topics in Cognitive Science. pdf html

Kominsky, J., Bascandziev, I., Shafto, P., & Bonawitz, E. (2023). Talk of the Town Mobile App Platform: New method engaging family in STEM learning and research in homes and communities. Frontiers in Psychology. html

Yang, S, C-H., Rank, C., Whritner, J., Nasraoui, O., & Shafto, P. (2023). Human variability and the explore-exploit tradeoff in recommendation. Cognitive Science. PsyArXiv html

Barak, L., Fernandez, N., Feldman, N., & Shafto, P. (2023) Modeling substitution errors in spanish morphology learning. Proceedings of the 45th annual conference of the Cognitive Science Society. html

2022

Chiu, W-T., Wang, P., & Shafto, P. (2022). Probabilistic inverse Optimal Transport. International Conference on Machine Learning (ICML). arXiv

Yang, S., C-H., Folke, T., & Shafto, P. (2022). A psychological theory of explainability. International Conference on Machine Learning (ICML). arXiv

Paranamana, P., Wang, P., & Shafto, P. (2022). Evolution of beliefs in social networks. Collective Intelligence. arXiv

Richard, B. & Shafto, P. (2022). Sensitivity to the slope (α) of the amplitude spectrum of natural scenes is dependent on the α of recently viewed environments: A visual adaptation study in modified reality. Vision Research. arXiv

Harmon, Z., Barak, L., Shafto, P., Edwards, J., & Feldman, N. (2022). The competition–compensation account of Developmental Language Disorder. Developmental Science. html

Bokadia, H., Yang, S, C-H., Li, Z., Folke, T., & Shafto, P. (2022). Evaluating perceptual and semantic interpretability of saliency methods: A case study of melanoma. Applied AI Letters. html

Thomas, D., Kleinberg, S., Brown, A., Crow, M., Bastian, N., Reisweber, N., Lasater, R., Kendall, T., Shafto, P., Blaine, R., Smith, S., Ruiz, D., Morrell, C., & Clark, N. (2022). Model Machine Learning Practices to Support the Principles of AI and Ethics in Nutrition Research. Nutrition and Diabetes.

2021

Shafto, P., Wang, J., & Wang, P. (in press). Cooperative communication as Belief Transport. Trends in Cognitive Sciences. pdf

Yang, S.,C-H., Folke, T., & Shafto, P. (2021). Abstraction, validation, and generalization for explainable artificial intelligence. Applied AI Letters. https://doi.org/10.1002/ail2.37 arXiv html

Nguyen, K., Misra, D., Schapire, R., Dudík, M., & Shafto, P. (2021). Interactive learning from activity description. International Conference on Machine Learning (ICML). arXiv

Yang, S.,C-H., Vong, W-K., Sojitra, R.B., Folke, T., & Shafto, P. (2021). Mitigating belief projection in explainable artificial intelligence via Bayesian Teaching. Scientific Reports. pdf arXiv

Lu, C-K & Shafto, P. (2021). Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning. Entropy, 23, 1387. doi.org: 10.3390/e23111387 html arXiv

Lu, C-K & Shafto, P. (2021). Conditional Deep Gaussian Processes: multi-fidelity kernel learning. Entropy. arXiv

Folke, T., Yang, S.C-H., Anderson, S., & Shafto, P. (2021). Explainable AI for medical imaging: explaining pneumothorax diagnoses with Bayesian teaching. Proc. SPIE 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III. doi: 10.1117/12.2585967 arXiv

Kominsky, J., Shafto, P., & Bonawitz, E.B. (2021). There’s something inside: Children’s intuitions about animate agents. PLOS ONE. pdf

Colantonio, J.A., Durkin, K., Caglar, L.R., Shafto, P., & Bonawitz, E. (2021). The intentional selection assumption. Frontiers in Psychology, 12, doi: 10.3389/fpsyg.2021.569275 html

Bascandziev, I., Shafto, P., & Bonawitz, E.B. (2021). The sound of pedagogical questions. Proceedings of the 43rd annual conference of the Cognitive Science Society.

Harmon, Z., Barak, L., Shafto, P., Edwards, J., & Feldman, N. (2021). Making Heads or Tails of it: A competition–compensation account of morphological deficits in language impairment. Proceedings of the 43rd annual conference of the Cognitive Science Society.

2020

Wang, P., Wang, J., Paranamana, P., & Shafto, P. (2020). A mathematical theory of cooperative communication. Advances in Neural Information Processing Systems (NeurIPS). arXiv (oral presentation, <1.5% acceptance rate)

Wang, J., Wang, P., & Shafto, P. (2020). Sequential cooperative Bayesian inference. International Conference on Machine Learning (ICML). arXiv

Wang, P., Givchi, A., & Shafto, P. (2020). Manifold learning from a teacher’s demonstrations. NeurIPS workshop: TDA and beyond. arXiv

Lu, C-K, Yang, S, C-H, Hao, X., & Shafto, P. (2020). Interpretable deep Gaussian Processes with moments. Proceedings of the 23rd international conference on Artificial Intelligence and Statistics (AIStats). AIStats arXiv

Daubert, E.N., Yu, Y., Grados, M., Shafto, P., Bonawitz, L.B. (2020). Pedagogical questions promote causal learning in preschoolers. Scientific reports.

Yu, Y., Shafto, P., & Bonawitz, E. (2020). Inconvenient samples: Modeling biases related to parental consent by coupling observational and experimental results. Open Mind, 4, 13-24.

Sun, W-L., Nasraoui, O., & Shafto, P. (2020). Evolution and impact of bias in human and machine learning algorithm interaction. PLoS one, 15(8), e0235502.

Bonawitz, E., Shafto, P., Yu, Y., Gonzalez, A. & Bridgers, S. (2020). Children change their answers in response to neutral follow-up questions by a knowledgeable asker. Cognitive Science. doi: 10.1111/cogs.12811

Barak, L., Yang, S, C-H., Rank, C. & Shafto, P. (2020). Replicating L2 learning in a computational model. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.

2019

Richard, B., Hansen, B.C., Johnson, A.P., & Shafto, P. (2019). Spatial summation of broadband contrast. Journal of Vision, 19(5), 1-19. pdf

Wang, P., Paranamana, P., & Shafto, P. (2019). Generalizing the theory of cooperative inference. Proceedings of the 22nd international conference on Artificial Intelligence and Statistics (AISTATS). arXiv

Yu, Y., Bonawitz, L.B., & Shafto, P. (2019). Pedagogical questions in parent-child conversations. Child Development, 90(1), 147-161. doi:10.1111/cdev.12850 pdf

Jean, A., Daubert, E., Yu, Y., Shafto, P., & Bonawitz, E.B. (2019). Pedagogical questions empower exploration. Proceedings of the 41st annual conference of the Cognitive Science Society. pdf

Yang, S.C-H., Vong, W.K., Yu, Y., & Shafto, P. (2019). A unifying computational framework for teaching and active learning. Topics in Cognitive Science. doi: https://doi.org/10.1111/tops.12405 pdf code

Sun, W., Khenissi, S., Nasraoui, O. & Shafto, P. (2019). Debiasing collaborative filtering recommender systems. The Third International Workshop on Augmenting Intelligence with Bias-Aware Humans-in-the–Loop (HumBL@WWW2019).

Williams, J.D., Lopez, D., Shafto, P., Lee, K. (2019). Technological workforce and Its impact on algorithmic justice in politics. Consumer Needs and Solutions, 6: 84. doi: 10.1007/s40547-019-00103-3

Bass, I., Gopnik, A., Hanson, M., Ramarajan, D., Shafto, P., Wellman, H., & Bonawitz, E.B. (2019). Children’s developing theory of mind and pedagogical evidence selection. Developmental Psychology, 55(2), 86-302. doi: 10.1037/dev0000642 PsyArxiv.

2018

Lu, C-K. Yang, S.C-H., & Shafto, P. (2018). Standing wave decomposition Gaussian Process. Physical Review E, 98, 032303. arXiv

Yang, S.C-H., Yu, Y., Givchi, A., Wang, P., Vong, W.K., & Shafto, P. (2018). Optimal cooperative inference. Proceedings of the 21st international conference on Artificial Intelligence and Statistics (AISTATS). arXiv

Gweon, H., Shafto, P., & Schulz, L.E. (2018). Development of children’s sensitivity to over-informativeness in learning and teaching. Developmental Psychology, 54(11), 2113-2125. doi: http://dx.doi.org/10.1037/dev00005802113 PDF

Yu, Y., Landrum, A., Bonawitz, L.B., & Shafto, P. (2018). Questioning supports effective transmission of knowledge and increased exploratory learning in pre-kindergarten children. Developmental Science. doi:10.1111/desc.12696 PDF

Yu, Y., Shafto, P., Bonawitz, E.B., Yang, S.C-H., Golinkoff, R.M., Corriveau, K.H., Hirsh-Pasek, K., & Xu, F. (2018). The theoretical and methodological opportunities afforded by guided play. Frontiers in Psychology, 9:1152. doi:10.3389/fpsyg.2018.01152 PDF

Vong, W-K., Sojitra, R., Reyes, A., Yang, S.C-H., & Shafto, P. (2018). Bayesian teaching of image categories. Proceedings of the 40th annual conference of the Cognitive Science Society. PDF

Choi, K., Lapidow, E., Austin, J., Shafto, P., & Bonawitz, E.B. (2018). Preschoolers are more likely to direct questions to adults than to other children (or selves) during spontaneous conversational acts. Proceedings of the 40th annual conference of the Cognitive Science Society. PDF

Bass, I., Shafto, P., & Bonawitz, E.B. (2018). That’ll teach ‘em: How expectations about teaching styles may constrain inferences. Proceedings of the 40th annual conference of the Cognitive Science Society. PDF

Perfors, A., Navarro, D.J., & Shafto, P. (2018). Stronger evidence isn’t always better: A role for social inference in evidence selection and interpretation. Proceedings of the 40th annual conference of the Cognitive Science Society. PDF

Sun, W., Nasraoui, O. & Shafto, P. (2018). Iterated algorithmic bias in the interactive machine learning process of information filtering. Proceedings of the 10th international conference on Knowledge Discovery and Information Retrieval (KDIR). PDF Best paper award winner

Badami, M., Nasraoui, O. & Shafto, P. (2018). PrCP: Pre-recommendation counter-polarization. Proceedings of the 10th international conference on Knowledge Discovery and Information Retrieval (KDIR). PDF

2017

Yang, S.C-H. & Shafto, P. (2017). Explanable Artificial Intelligence via Bayesian Teaching. NIPS 2017 workshop on Teaching Machines, Robots, and Humans. PDF

Lane, J. & Shafto, P. (2017). Preschoolers and toddlers attribute causal power to novel invisible entities. Journal of Experimental Child Psychology, 162, 268-281. PDF

Baker, L., LoBue, V., Bonawitz, E.B. & Shafto, P. (2017). Towards automated classification of emotional facial expressions. Proceedings of the 39th annual conference of the Cognitive Science Society. PDF

Yang, S.C-H. & Shafto, P. (2017). Teaching versus active learning: A computational analysis of conditions that affect learning. Proceedings of the 39th annual conference of the Cognitive Science Society. PDF

Yang, S.C-H., Whritner, J.A., Nasraoui, O. & Shafto, P. (2017). Unifying recommendation and active learning for human-algorithm interactions. Proceedings of the 39th annual conference of the Cognitive Science Society. PDF

Yu, Y., Bonawitz, E.B. & Shafto, P. (2017). Inconvenient samples: Modeling the effects of non-consent by coupling observational and experimental results. Proceedings of the 39th annual conference of the Cognitive Science Society. PDF

Bass, I., Bonawitz, L.B., Shafto, P., Ramarajan, D., Gopnik, A. & Wellman, H. (2017). I know what you need to know: Children’s developing theory of mind and pedagogical evidence selection. Proceedings of the 39th annual conference of the Cognitive Science Society. PDF

Badami, M., Nasraoui, O., Sun. W., & Shafto, P. (2017). Detecting polarization in ratings: An automated pipeline and a preliminary quantification on several benchmark data sets. IEEE Big Data 2017, International Workshop on Big Social Media Data Management and Analysis. PDF

Schweinhart, A.M., Shafto, P. & Essock, E.A. (2017). Distribution of content in recently-viewed scenes whitens perception. Journal of Vision, 17(3), 8-8 PDF

Eaves, B.S. & Shafto, P. (2017). Parameterizing developmental changes in epistemic trust. Psychonomic Bulletin & Review, 24(2), 277-306. PDF

McCrink, K., Shafto, P. & Barth, H. (2017). The relationship between non-symbolic multiplication and division in childhood. Quarterly Journal of Experimental Psychology, 70(4), 686-702.

2016

Shafto, P. & Nasraoui, O. (2016). Human-recommender systems: From benchmark data to benchmark cognitive models. Proceedings of the 10th ACM Conference on Recommender Systems (RecSys 2016), 127-130. PDF

Eaves, B.S. & Shafto, P. (2016). Toward a general, scaleable framework for Bayesian teaching with applications to topic models. IJCAI 2016 workshop on Interactive Machine Learning: Connecting Humans and Machines. PDF, CODE

Schweinhart, A., Eaves, B.S. & Shafto, P. (2016). Automating the recoding, analysis, and interpretation pipeline using naturalistic visual scenes. IJCAI 2016 workshop on Closing the Cognitive Loop: Third Workshop on Knowledge, Data, and Systems for Cognitive Computing. PDF

Searcy, S. R. & Shafto, P. (2016). Cooperative Inference: Features, objects, and collections. Psychological Review, 123(5), 510-533. PDF

Eaves, B.S., Feldman, N., Griffiths, T. & Shafto, P. (2016). Infant-directed speech is consistent with teaching. Psychological Review, 123(6), 758-771. PDF

Mansinghka, V.K., Shafto, P., Jonas, E., Petschulat, C., Gasner, M. & Tenenbaum, J.B. (2016). CrossCat: A fully Bayesian nonparametric method for analyzing heterogeneous, high dimensional data. Journal of Machine Learning Research, 17, 1-49. arXiv

Eaves B.S., Schweinhart A., & Shafto P. (2016). Tractable Bayesian teaching. In M.N. Jones (Ed.), Big Data in Cognitive Science. New York, NY: Psychology Press. PDF

Nasraoui, O. & Shafto, P. (2016). Human-algorithm interaction biases in the big data cycle: A markov chain iterated learning framework. arXiv preprint arxiv:1608.07895 arXiv

Yu, Y., Bonawitz, E. & Shafto, P. (2016). Questions in informal teaching: A study of mother-child conversations. Proceedings of the 38th Annual Conference of the Cognitive Science Society. PDF

Bonawitz, E. B. & Shafto, P. (2016). Computational models of development, Social influences. Current Opinion in Behavioral Sciences, 7, 95-100. PDF

Durkin, K. & Shafto, P. (2016). Epistemic trust and education: Effects of informant reliability on student learning of decimal concepts. Child Development, 87, 154–164. PDF

2015

Mansinghka, V., Tibbetts, R., Baxter, J., Shafto, P. & Eaves, B. (preprint). BayesDB: A probabilistic programming system for querying the probable implications of data. arXiv preprint arXiv:1512.05006. arXiv

Shafto, P. & Bonawitz, L.B. (2015). Choice from among intentionally selected options. In Ross, B. (Ed.) Psychology of Learning and Motivation Volume 63, San Diego: Elsevier. PDF

Rafferty, A., Brunskill, E., Griffiths, T.L. & Shafto, P. (2015). Faster teaching via POMDP planning. Cognitive Science. PDF

Rhodes, M., Bonawitz, E., Shafto, P., Chen, A. & Caglar, L. (2015). Controlling the message: preschoolers’ use of information to teach and deceive others. Frontiers in Psychology. 6:867. PDF

Durkin, K., Caglar, L.R., Bonawitz, E. & Shafto, P. (2015). Explaining Choice Behavior: The Intentional Selection Assumption. Proceedings of the 37th Annual Conference of the Cognitive Science Society. PDF

Noles, N.S., Danovitch, J.H. & Shafto, P. (2015). Children’s Trust in Technological and Human Informants. Proceedings of the 37th Annual Conference of the Cognitive Science Society. PDF

Landrum, A.R., Cloudy, J. & Shafto, P. (2015). More than true: Developmental changes in use of the inductive strength for selective trust. Proceedings of the 37th Annual Conference of the Cognitive Science Society. PDF

Landrum, A.R. Eaves Jr, B.S. & Shafto, P. (2015). Learning to trust and trusting to learn: a theoretical framework. Trends in Cognitive Sciences, 19, 109-111. PDF

2014

Rhodes, M., Bonawitz, E., Shafto, P. & Chen, A. (2014). Controlling the message: Preschoolers’ use of evidence to teach and deceive others. Proceedings of the 36th Annual Conference of the Cognitive Science Society. PDF

Gweon, H., Shafto, P. & Schulz, L.E. (2014). Children consider prior knowledge and the cost of information both in learning from and teaching others. Proceedings of the 36th annual conference of the Cognitive Science Society. PDF

Eaves, B.S. & Shafto, P. (2014). Order effects in learning relational structures. Proceedings of the 36th annual conference of the Cognitive Science Society. PDF

Searcy, S. R. & Shafto, P. (2014). Learning biases for teaching boolean concepts. Proceedings of the 36th annual conference of the Cognitive Science Society. PDF

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

2012

Eaves, B. & Shafto, P. (2012). Unifying pedagogical reasoning and epistemic trust. In Xu., F. and Kushnir, T. (Eds.) Advances in Child Development and Behavior, 43, 295-319. PDF

Shafto, P., Goodman, N.D. & Frank, M.C. (2012). Learning from others: The consequences of psychological reasoning for human learning. Perspectives on Psychological Science, 7, 341-351. PDF

Shafto, P., Eaves, B., Navarro, D.J. & Perfors, A. (2012). Epistemic trust: Modeling children’s reasoning about others’ knowledge and intent. Developmental Science, 15, 436-447. PDF

Kemp, C., Shafto, P. & Tenenbaum, J.B. (2012). An integrated account of generalization across objects and features. Cognitive Psychology, 64, 35-73. PDF

Shafto, P., Gweon, H., Fargen, C. & Schulz, L. (2012). Enough is enough: Inductive sufficiency guides learners’ ratings of informant helpfulness. Proceedings of the 34th annual conference of the Cognitive Science Society. PDF

Gonzalez, A., Shafto, P., Bonawitz, E.B. & Gopnik, A. (2012). Is that your final answer? The effects of neutral queries on children’s choices. Proceedings of the 34th annual conference of the Cognitive Science Society. PDF

2011

Bonawitz, E.B., Shafto, P., Gweon, H., Goodman, N.D., Spelke, E. & Schulz, L. (2011). The double-edged sword of pedagogy: Instruction affects spontaneous exploration and discovery. Cognition, 120, 322-330. PDF

Shafto, P., Kemp, C., Mansinghka, V.K. & Tenenbaum, J.B. (2011). A probabilistic model of cross-categorization. Cognition, 120, 1-25. PDF

Buchbaum, D., Griffiths, T.L., Gopnik, A. & Shafto, P. (2011). Children’s imitation of causal action sequences is influenced by statistical and pedagogical evidence. Cognition, 120, 331-340. PDF

Warner, R., Stoess, T. & Shafto, P. (2011). Reasoning about teaching and misleading situations. Proceedings of the 33rd annual conference of the Cognitive Science Society. PDF

Montague, R., Navarro, D.J., Perfors, A., Warner, R. & Shafto, P. (2011). To catch a liar: The effects of truthful and deceptive testimony on inferential learning. Proceedings of the 33rd annual conference of the Cognitive Science Society. PDF

Smith, N.A. & Shafto, P. (2011). The role of cross-cutting systems of categories in category-based induction. Proceedings of the 33rd annual conference of the Cognitive Science Society. PDF

Rafferty, A., Brunskill, E., Shafto, P. & Griffiths, T.L. (2011). Faster teaching by POMDP planning. Proceedings of the 15th international conference on Artificial Intelligence in Education (AIED). PDF

Li, D. & Shafto, P. (2011). Bayesian hierarchical cross-clustering. Proceedings of the 14th international conference on Artificial Intelligence and Statistics (AISTATS). PDF

2010

Shafto, P., Goodman, N.D., Gerstle, B. & Ladusaw, F. (2010). Prior expectations in pedagogical situations. Proceedings of the 32nd annual conference of the Cognitive Science Society. PDF

Li, D., Rouchka, E. & Shafto, P. (2010). Phylogenomic analysis using Bayesian congruence measuring. Proceedings of the 2nd International Conference on Bioinformatics and Computation (BICoB). PDF

2009

Bonawitz, E.B., Shafto, P., Gweon, H., Chang, I. Katz, S. & Schulz, L. (2009). The double-edged sword of pedagogy: Modeling the effect of pedagogical contexts on preschoolers’ exploratory play. Proceedings of the 31st annual meeting of the Cognitive Science Society. PDF

Warner, R. Shafto, P., Baker, C.L. & Tenenbaum, J.B. (2009). Abstract knowledge guides prediction and search in novel situations. Proceedings of the 31st annual meeting of the Cognitive Science Society. PDF

2008

Shafto, P., Kemp, C., Bonawitz, E.B., Coley, J.D. & Tenenbaum, J.B. (2008). Inductive reasoning about causally transmitted properties. Cognition. 109, 175-192. PDF

Shafto, P. & Goodman, N. (2008). Teaching games: Statistical sampling assumptions for learning in pedagogical situations. Proceedings of the 30th annual conference of the Cognitive Science Society. PDF

2007

Mansinghka, V.K., Jonas, E., Petschulat, C., Cronin, B., Shafto, P. & Tenenbaum, J.B. (2007). Cross-Categorization: A method for discovering multiple overlapping clusterings, NIPS workshop PDF

Tenenbaum, J.B., Kemp, C. & Shafto, P. (2007). Theory-based Bayesian models of inductive reasoning. In Feeney, A. & Heit, E. (Eds.), Induction. Cambridge, U.K.: Cambridge University Press. PDF

Shafto, P., Vitkin, A. & Coley, J.D. (2007). Availability in category-based induction. In Feeney, A. & Heit, E. (Eds.), Induction. Cambridge, U.K.: Cambridge University Press. PDF

Feeney, A., Shafto, P. & Dunning, D. (2007). Who is susceptible to the conjunction fallacy in category-based induction? Psychonomic Bulletin & Review, 14, 884-889. PDF

Shafto, P., Coley, J.D. & Baldwin, D. (2007). Effects of time pressure on context-sensitive property induction. Psychonomic Bulletin & Review, 14, 890-894. PDF

2006

Kemp, C., Shafto, P., Berke, A. & Tenenbaum, J.B. (2006). Combining causal and similarity-based reasoning. Advances in Neural Information Processing Systems. Best Student Paper, Honorable Mention, NIPS 2006. PDF

Shafto, P., Kemp, C., Mansinghka, V.K., Gordon, M. & Tenenbaum, J.B. (2006). Learning cross-cutting systems of categories. Proceedings of the 28th annual conference of the Cognitive Science Society. PDF

2005

Shafto, P., Kemp, C., Baraff, E., Coley, J.D. & Tenenbaum, J.B. (2005). Context-sensitive induction. Proceedings of the 27th annual conference of the Cognitive Science Society. PDF

Coley, J.D., Shafto, P., Stepanova, O. & Baraff, E. (2005). Knowledge and category-based induction. In Ahn, W., Goldstone, R.L., Love, B.C., Markman, A.B. & Wolff, P. (Eds.), Categorization inside and outside the laboratory: Essays in honor of Douglas L. Medin. Washington, DC: American Psychological Association. PDF

2003

Shafto, P. & Coley, J.D. (2003). Development of categorization and reasoning in the natural world: Novices to experts, naive similarity to ecological knowledge. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 641-649. PDF

2002

Coley, J.D., Solomon, G.E.A. & Shafto, P. (2002). The development of folkbiology: A cognitive science perspective on children’s understanding of the biological world. In Kahn, P. & Kellert, S. (Eds.), Children and nature: Psychological, sociocultural, and evolutionary investigations (65-91). Cambridge, MA: MIT Press. PDF

2001

Ahn, W., Kalish, C., Gelman, S.A., Medin, D.L., Luhmann, C., Atran, S., Coley, J.D. & Shafto, P. (2001). Why essences are essential in the psychology of concepts. Cognition, 82, 59-69. PDF