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.

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

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Peres, F., Smith, K. A. & Tenenbaum, J. B. Rapid Physical Predictions from Convolutional Neural Networks. Neural Information Processing Systems, Intuitive Physics Workshop (2016). at <http://phys.csail.mit.edu/papers/9.pdf>

Rapid Physical Predictions - NIPS Physics Workshop Poster (1.47 MB)

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Chu, J., Gauthier, J., Levy, R., Tenenbaum, J. B. & Schulz, L. Query-guided visual search . 41st Annual conference of the Cognitive Science Society (2019).

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Schulz, E., Tenenbaum, J. B., Duvenaud, D., Speekenbrink, M. & Gershman, S. J. Probing the compositionality of intuitive functions. (2016).

CBMM-Memo-048.pdf (815.72 KB)

Kryven, M., Ullman, T. D., Cowan, W. & Tenenbaum, J. B. Plans or Outcomes: How Do We Attribute Intelligence to Others?. Cognitive Science 45, (2021).

Kulkarni, T., Kohli, P., Tenenbaum, J. B. & Mansinghka, V. Picture: An Imperative Probabilistic Programming Language for Scene Perception. Computer Vision and Pattern Recognition (2015).

Yildirim, I., Gerstenberg, T., Saeed, B., Toussant, M. & Tenenbaum, J. B. Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints. Proceedings of the 39th Annual Conference of the Cognitive Science Society (2017).

Physical problem solving Joint planning with symbolic, geometric, and dynamic constraints, Yildirim et al., 2017.pdf (2.46 MB)

Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Eventsfor Machine Social Perception. Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020 (2020). at <https://openreview.net/forum?id=_bokm801zhx>

phase_physically_grounded_abstract_social_events_for_machine_social_perception.pdf (2.49 MB)

Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception. (2021).

CBMM-Memo-123.pdf (3.08 MB)

Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception. AAAI-21 (2021).

Yildirim, I., Siegel, M. H., Soltani, A. A., Chaudhuri, S. Ray & Tenenbaum, J. B. Perception of 3D shape integrates intuitive physics and analysis-by-synthesis. Nature Human Behaviour (2023). doi:10.1038/s41562-023-01759-7

Yildirim, I., Siegel, M. & Tenenbaum, J. B. Perceiving Fully Occluded Objects with Physical Simulation. Cognitive Science Conference (CogSci) (2015).

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Sheskin, M. et al. Online Developmental Science to Foster Innovation, Access, and Impact. Trends in Cognitive Sciences 24, 675 - 678 (2020).

Barbu, A. et al. ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models. Neural Information Processing Systems (NeurIPS 2019) (2019).

9142-objectnet-a-large-scale-bias-controlled-dataset-for-pushing-the-limits-of-object-recognition-models.pdf (16.31 MB)

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

NotSoInnocent_InPress.pdf (238.53 KB)

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

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>

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

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).

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).

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)

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

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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).

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)

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

krafft_aaai2016.pdf (247.58 KB)

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)

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