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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 Joshua B. Tenenbaum [Clear All Filters]

Conference Paper

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. AAAI-21 (2021).

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

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)

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)

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>

Allen, K., Yildirim, I. & Tenenbaum, J. B. Integrating Identification and Perception: A case study of familiar and unfamiliar face processing. Proceedings of the Thirty-Eight Annual Conference of the Cognitive Science Society (2016).

allen_5_13.pdf (2.13 MB)

Tsividis, P., Pouncy, T., Xu, J. L., Tenenbaum, J. B. & Gershman, S. J. Human Learning in Atari. AAAI Spring Symposium Series (2017).

Tsividis et al - Human Learning in Atari.pdf (844.47 KB)

Zhang, Z. et al. Generative modeling of audible shapes for object perception. The IEEE International Conference on Computer Vision (ICCV) (2017). at <http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Generative_Modeling_of_ICCV_2017_paper.html>

Wu, J., Yildirim, I., Lim, J. J., Freeman, W. T. & Tenenbaum, J. B. Galileo: Perceiving physical object properties by integrating a physics engine with deep learning. NIPS 2015 (2015). at <https://papers.nips.cc/paper/5780-galileo-perceiving-physical-object-properties-by-integrating-a-physics-engine-with-deep-learning>

Smith, K. A. et al. The fine structure of surprise in intuitive physics: when, why, and how much?. Proceedings of the 42th Annual Meeting of the Cognitive Science Society - Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020, virtual, July 29 - August 1, 2020 (Denison, S., Mack, M., Xu, Y. & Armstrong, B. C.) (2020). at <https://cogsci.mindmodeling.org/2020/papers/0761/index.html>

Ullman, T., Tenenbaum, J. B. & Spelke, E. S. Effort as a bridging concept across action and action understanding: Weight and Physical Effort in Predictions of Efficiency in Other Agents. International Conference on Infant Studies (ICIS) (2016).

Yildirim, I., Kulkarni, T., Freiwald, W. A. & Tenenbaum, J. B. Efficient and robust analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations. Annual Conference of the Cognitive Science Society (2015).

yildirimetal_cogsci15.pdf (3.22 MB)

Kleiman-Weiner, M., Ho, M. K., Austerweil, J. L., L, L. Michael & Tenenbaum, J. B. Coordinate to cooperate or compete: abstract goals and joint intentions in social interaction. Proceedings of the 38th Annual Conference of the Cognitive Science Society (2016).

kleiman2016coordinate.pdf (266.87 KB)

Yildirim, I. & Janner, M. Causal and compositional generative models in online perception. 39th Annual Conference of the Cognitive Science Society (Belledonne, M., Wallraven, C., Freiwald, W. A. & Tenenbaum, J. B.) (2017).

yildirim_janner_2_1.pdf (6.88 MB)

Conference Abstract

Yildirim, I., Kulkarni, T., Freiwald, W. A. & Tenenbaum, J. B. Explaining Monkey Face Patch System as Efficient Analysis-by-Synthesis. (2014).

yildirimetal_cosyne15.pdf (313.57 KB)

Kryven, M., Scholl, B. & Tenenbaum, J. B. Does intuitive inference of physical stability interruptattention?. Cognitive Sciences Society (2019).

Kryven, M., Niemi, L., Paul, L. & Tenenbaum, J. B. Choosing a Transformative Experience . Cognitive Sciences Society (2019).

Code

Schwartz, J. et al. ThreeDWorld (TDW): A High-Fidelity, Multi-Modal Platform for Interactive Physical Simulation. (2020). at <http://www.threedworld.org/>

CBMM Memos

Gao, T., Harari, D., Tenenbaum, J. B. & Ullman, S. When Computer Vision Gazes at Cognition. (2014).

CBMM-Memo-025.pdf (3.78 MB)

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)

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)

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)

Tejwani, R. et al. Incorporating Rich Social Interactions Into MDPs. (2022).

CBMM-Memo-133.pdf (1.68 MB)

Goodman, N. D., Tenenbaum, J. B. & Gerstenberg, T. Concepts in a Probabilistic Language of Thought. (2014).

CBMM-Memo-010.pdf (902.53 KB)

Pages