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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Found 103 results

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

2020

Allen, K., Smith, K. A. & Tenenbaum, J. B. Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning. Proceedings of the National Academy of Sciences 201912341 (2020). doi:10.1073/pnas.1912341117

1912341117.full_.pdf (2.15 MB)

Dasgupta, I., Schulz, E., Tenenbaum, J. B. & Gershman, S. J. A theory of learning to infer. Psychological Review 127, 412 - 441 (2020).

Gen, C. et al. ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. arXiv (2020). at <https://arxiv.org/abs/2007.04954>

2007.04954.pdf (7.06 MB)

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

Eisape, T., Levy, R., Tenenbaum, J. B. & Zaslavsky, N. Toward human-like object naming in artificial neural systems . International Conference on Learning Representations (ICLR 2020), Bridging AI and Cognitive Science workshop (2020).

2019

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

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

Ullman, T. D. et al. Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects. Cognitive Science Society (2019). at <https://mindmodeling.org/cogsci2019/papers/0506/index.html>

Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects.pdf (2.62 MB)

Serrino, J., Kleiman-Weiner, M., Parkes, D. C. & Tenenbaum, J. B. Finding Friend and Foe in Multi-Agent Games. Neural Information Processing Systems (NeurIPS 2019) (2019).

Max KW paper.pdf (928.96 KB)

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).

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)

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)

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

Fazeli, N. et al. See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion. Science Robotics 4, eaav3123 (2019).

Han, C., Mao, J., Gan, C., Tenenbaum, J. B. & Wu, J. Visual Concept-Metaconcept Learning. Neural Information Processing Systems (NeurIPS 2019) (2019).

8745-visual-concept-metaconcept-learning.pdf (1.92 MB)

Ellis, K. et al. Write, Execute, Assess: Program Synthesis with a REPL. Neural Information Processing Systems (NeurIPS 2019) (2019).

9116-write-execute-assess-program-synthesis-with-a-repl.pdf (3.9 MB)

2018

Toussaint, M., Allen, K., Smith, K. A. & Tenenbaum, J. B. Differentiable physics and stable modes for tool-use and manipulation planning. Robotics: Science and Systems 2018 (2018).

ToussaintEtAl_DiffPhysStable.pdf (1.97 MB)

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>

1804.04604v1.pdf (488.85 KB)

Belbute-Peres, Fde Avila, Smith, K. A., Allen, K., Tenenbaum, J. B. & Kolter, Z. End-to-end differentiable physics for learning and control. Advances in Neural Information Processing Systems 31 (NIPS 2018) (2018).

7948-end-to-end-differentiable-physics-for-learning-and-control.pdf (794.17 KB)

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)

Gerstenberg, T. et al. Lucky or clever? From changed expectations to attributions of responsibility. Cognition (2018).

Wu, Y., Baker, C., Tenenbaum, J. B. & Schulz, L. Rational inference of beliefs and desires from emotional expressions. Cognitive Science 42, (2018).

Wu_Baker_Tenenbaum_Schulz_in_press_cognitive_science.pdf (1.65 MB)

Hamrick, J. B. et al. Relational inductive bias for physical construction in humans and machines. In Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci 2018) (2018).

1806.01203.pdf (1022.51 KB)

2017

Lake, B. M., Ullman, T. D., Tenenbaum, J. B. & Gershman, S. J. Building machines that learn and think like people. Behavioral and Brain Sciences 40, e253 (2017).

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