Publication

Found 113 results
Author Title [ Type(Desc)] Year
Filters: Author is Tenenbaum, Joshua B.  [Clear All Filters]
Journal Article
Gershman, S. J., Tenenbaum, J. B. & Jaekel, F. Discovering hierarchical motion structure. Vision Research Available online 26 March 2015, (2015).PDF icon hierarchical_motion.pdf (582.01 KB)
Harari, D., Tenenbaum, J. B. & Ullman, S. Discovery and usage of joint attention in images. arXiv.org (2018). at <https://arxiv.org/abs/1804.04604>PDF icon 1804.04604v1.pdf (488.85 KB)
Mahowald, K. et al. Dissociating language and thought in large language models. Trends in Cognitive Sciences 28, 517 - 540 (2024).
Yildirim, I., Belledonne, M., Freiwald, W. A. & Tenenbaum, J. B. Efficient inverse graphics in biological face processing. Science Advances 6, eaax5979 (2020).PDF icon eaax5979.full_.pdf (3.22 MB)
Houlihan, S. Dae, Kleiman-Weiner, M., Hewitt, L. B., Tenenbaum, J. B. & Saxe, R. Emotion prediction as computation over a generative theory of mind. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 381, (2023).PDF icon houlihan2023computedappraisals.pdf (2.37 MB)
Gerstenberg, T., Peterson, M. F., Goodman, N. D., Lagnado, D. A. & Tenenbaum, J. B. Eye-Tracking Causality. Psychological Science (2017).PDF icon eye_tracking_causality.pdf (8.04 MB)
Gerstenberg, T., Peterson, M. F., Goodman, N. D., Lagnado, D. A. & Tenenbaum, J. B. Eye-Tracking Causality. Psychological Science 73, (2017).
Fischer, J., Mikhael, J. G., Tenenbaum, J. B. & Kanwisher, N. Functional neuroanatomy of intuitive physical inference. Proceedings of the National Academy of Sciences 113, E5072 - E5081 (2016).
Singhal, U. et al. How to Guess a Gradient. arXiv (2023). at <https://arxiv.org/abs/2312.04709>
Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B. Human-level concept learning through probabilistic program induction. Science 350, 1332-1338 (2015).
Yildirim, I., Wu, J., Kanwisher, N. & Tenenbaum, J. B. An integrative computational architecture for object-driven cortex. Current Opinion in Neurobiology 55, 73 - 81 (2019).
Schwettmann, S., Tenenbaum, J. B. & Kanwisher, N. Invariant representations of mass in the human brain. eLife 8, (2019).
Ullman, T. D., Stuhlmüller, A., Goodman, N. D. & Tenenbaum, J. B. Learning physical parameters from dynamic scenes. Cognitive Psychology 104, 57-82 (2018).PDF icon T-Ullman-etal_CogPsych_LearningPhysicalParametersFromDynamicScenes.pdf (3.15 MB)
Allen, K. R. et al. Lifelong learning of cognitive styles for physical problem-solving: The effect of embodied experienceAbstract. Psychonomic Bulletin & Review (2023). doi:10.3758/s13423-023-02400-4
Levine, S., Kleiman-Weiner, M., Schulz, L., Tenenbaum, J. B. & Cushman, F. A. The logic of universalization guides moral judgment. Proceedings of the National Academy of Sciences (PNAS) 202014505 (2020). doi:10.1073/pnas.2014505117
Gerstenberg, T. et al. Lucky or clever? From changed expectations to attributions of responsibility. Cognition (2018).
Zhou, L., Smith, K., Tenenbaum, J. B. & Gerstenberg, T. Mental Jenga: A counterfactual simulation model of causal judgments about physical support. PsyArXiv (2022). at <https://psyarxiv.com/4a5uh>
Allen, K. et al. Meta-strategy learning in physical problem solving: the effect of embodied experience. bioRxiv (2021).PDF icon 2021.07.08.451333v2.full_.pdf (3.05 MB)
Ullman, T. D., Spelke, E. S., Battaglia, P. & Tenenbaum, J. B. Mind Games: Game Engines as an Architecture for Intuitive Physics. Trends in Cognitive Science 21, 649 - 665 (2017).PDF icon Preprint submitted to Trends in Cognitive Science (17.64 MB)
Sosa, F. A., Ullman, T., Tenenbaum, J. B., Gershman, S. J. & Gerstenberg, T. Moral dynamics: Grounding moral judgment in intuitive physics and intuitive psychology. Cognition 217, 104890 (2021).
Jara-Ettinger, J., Gweon, H., Schulz, L. & Tenenbaum, J. B. The naive utility calculus: computational principles underlying social cognition. Trends Cogn Sci. (2016). doi:10.1016/j.tics.2016.05.011
Schrimpf, M. et al. The neural architecture of language: Integrative modeling converges on predictive processing. Proceedings of the National Academy of Sciences 118, e2105646118 (2021).
Tomov, M. S., Tsividis, P. A., Pouncy, T., Tenenbaum, J. B. & Gershman, S. J. The neural architecture of theory-based reinforcement learning. Neuron 111, 1331 - 1344.e8 (2023).
Puig, X., Shu, T., Tenenbaum, J. B. & Torralba, A. NOPA: Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistants. arXiv (2023). at <https://arxiv.org/abs/2301.05223>
Jara-Ettinger, J. Not So Innocent: Toddlers’ Inferences About Costs and Culpability. Psychological Science 26, 633-40 (2015).PDF icon NotSoInnocent_InPress.pdf (238.53 KB)

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