Publications

CBMM Memos were established in 2014 as a mechanism for our center to share research results with the wider scientific community. Click here to read more about the memos and to see a full list of the memos.

Videos
Support Us

Publication

Search

Show only items where

Author

Type

Term

Year

Keyword

Found 113 results

Filters: Author is Tenenbaum, Joshua B. [Clear All Filters]

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

I

Schwettmann, S., Tenenbaum, J. B. & Kanwisher, N. Invariant representations of mass in the human brain. eLife 8, (2019).

L

Tian, L., Ellis, K., Kryven, M. & Tenenbaum, J. B. Learning abstract structure for drawing by efficient motor program induction. Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020) (2020). at <https://papers.nips.cc/paper/2020/hash/1c104b9c0accfca52ef21728eaf01453-Abstract.html>

Nye, M., Solar-Lezama, A., Tenenbaum, J. B. & Lake, B. M. Learning Compositional Rules via Neural Program Synthesis. Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020) (2020). at <https://proceedings.neurips.cc/paper/2020/hash/7a685d9edd95508471a9d3d6fcace432-Abstract.html>

2003.05562.pdf (2.51 MB)

Ullman, T. D., Stuhlmüller, A., Goodman, N. D. & Tenenbaum, J. B. Learning physical parameters from dynamic scenes. Cognitive Psychology 104, 57-82 (2018).

T-Ullman-etal_CogPsych_LearningPhysicalParametersFromDynamicScenes.pdf (3.15 MB)

Wu, J., Lu, E., Kohli, P., Freeman, W. T. & Tenenbaum, J. B. Learning to See Physics via Visual De-animation. Advances in Neural Information Processing Systems 30 152–163 (2017). at <http://papers.nips.cc/paper/6620-learning-to-see-physics-via-visual-de-animation.pdf>

Learning to See Physics via Visual De-animation (1.11 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).

M

Wu, J. et al. MarrNet: 3D Shape Reconstruction via 2.5D Sketches. Advances in Neural Information Processing Systems 30 540–550 (2017). at <http://papers.nips.cc/paper/6657-marrnet-3d-shape-reconstruction-via-25d-sketches.pdf>

MarrNet: 3D Shape Reconstruction via 2.5D Sketches (6.25 MB)

Harari, D., Gao, T., Kanwisher, N., Tenenbaum, J. B. & Ullman, S. Measuring and modeling the perception of natural and unconstrained gaze in humans and machines. (2016).

CBMM-Memo-059.pdf (1.71 MB)

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).

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).

Preprint submitted to Trends in Cognitive Science (17.64 MB)

Smith, K. A. et al. Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) (2019). at <http: //physadept.csail.mit.edu/>

ADEPT_NeurIPS.pdf (11.07 MB)

Krafft, P., Baker, C., Pentland, A. & Tenenbaum, J. B. Modeling Human Ad Hoc Coordination. AAAI (2016).

krafft_aaai2016.pdf (247.58 KB)

Nakahashi, R., Baker, C. & Tenenbaum, J. B. Modeling human understanding of complex intentional action with a Bayesian nonparametric subgoal model. AAAI (2016).

nakahashi_aaai2016.pdf (1.74 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).

N

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

Bramley, N., Gerstenberg, T. & Tenenbaum, J. B. Natural science: Active learning in dynamic physical microworlds. 38th Annual Meeting of the Cognitive Science Society (2016).

Natural Science (Bramley, Gerstenberg, Tenenbaum, 2016).pdf (5.39 MB)

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).

Houlihan, S. Dae, Tenenbaum, J. B. & Saxe, R. The Neural Basis of Mentalizing: Linking Models of Theory of Mind and Measures of Human Brain Activity. 209 - 235 (Springer International Publishing, 2021). doi:10.1007/978-3-030-51890-510.1007/978-3-030-51890-5_11

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>

Puig, X., Shu, T., Tenenbaum, J. B. & Torralba, A. NOPA: Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistants. 2023 IEEE International Conference on Robotics and Automation (ICRA) (2023). doi:10.1109/ICRA48891.2023.10161352

Jara-Ettinger, J. Not So Innocent: Toddlers’ Inferences About Costs and Culpability. Psychological Science 26, 633-40 (2015).

NotSoInnocent_InPress.pdf (238.53 KB)

Pages