Joshua Tenenbaum

Joshua Tenenbaum
Joshua
Tenenbaum
Research Module Co-Leader
Department:  Brain and Cognitive Sciences

Associated Research Module: 

Associated Research Thrust: 

Joshua Tenenbaum is the Professor of Computational Cognitive Science, in the Brain and Cognitive Sciences Department, MIT.

Email:  jbt@mit.edu
Room:  46-4015

Current Advisees

Andres Campero Nunez - Graduate Student
Jon Gauthier - Graduate Student
Laila Johnston - Visiting Student
Marta Kryven - Postdoc
John Muchovej - Research Assistant
Vivian Paulun - Postdoc
Martin Schrimpf - Research Scientist
Max Siegel - Postdoc
Kevin Smith - Research Scientist
Amir Arsalan Soltani - Research Assistant
Felix Sosa - Graduate Student
Samuel C. Tenka - Graduate Student
Lucas Tian - Postdoc
Yang Wu - Graduate Student
Jun-Yan Zhu - Postdoc

Past Advisees

Kelsey Allen - Graduate Student
Peter Battaglia - Research Scientist
Mario Belledonne - Research Assistant
You-Jung Choi - Postdoc
Sholei Croom - Research Assistant, Lab Manager
Eyal Dechter - Graduate Student
Bernhard Egger - Postdoc
Kevin Ellis - Graduate Student
Nathalie Fernandez - PostBac/Visiting Student
Tobias Gerstenberg - Postdoc
Sean Dae Houlihan - Graduate Student
Max Kleiman-Weiner - Postdoc
Eliza Kosoy - Research Assistant
Owen Lewis - Graduate Student
Rachel Magid - Graduate Student
Jonathan Malmaud - Graduate Student
Tara Sofia Ramirez - PostBac/Visiting Student
Sarah Schwettmann - Postdoc
Pedro Tsividis - Postdoctoral Associate
Joey Velez-Ginorio - Visiting Student
Alejandro Vientos - PostBac/Visiting Student
Moyuru Yamada - Visiting Scientist
Ilker Yildirim - Research Scientist

Projects

CBMM Publications

J. Mao, Luo, Z., Gan, C., Tenenbaum, J. B., Wu, J., Kaelbling, L. Pack, and Ullman, T. D., Temporal and Object Quantification Networks, in Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, Canada, 2021.
Y. Du, Smith, K. A., Ullman, T., Tenenbaum, J. B., and Wu, J., Unsupervised Discovery of 3D Physical Objects, in International Conference on Learning Representations, 2021.
C. Bongiorno, Zhou, Y., Kryven, M., Theurel, D., Rizzo, A., Santi, P., Tenenbaum, J. B., and Ratti, C., Vector-based pedestrian navigation in cities, Nature Computational Science, vol. 1, no. 10, pp. 678 - 685, 2021.
K. A. Smith, Mei, L., Yao, S., Wu, J., Spelke, E. S., Tenenbaum, J. B., and Ullman, T. D., The fine structure of surprise in intuitive physics: when, why, and how much?, in 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, 2020.
I. Dasgupta, Schulz, E., Tenenbaum, J. B., and Gershman, S. J., A theory of learning to infer., Psychological Review, vol. 127, no. 3, pp. 412 - 441, 2020.
T. Eisape, Levy, R., Tenenbaum, J. B., and Zaslavsky, N., Toward human-like object naming in artificial neural systems , in International Conference on Learning Representations (ICLR 2020), Bridging AI and Cognitive Science workshop, Virtual conference (due to Covid-19), 2020.
L. Tian, Ellis, K., Kryven, M., and Tenenbaum, J. B., Learning abstract structure for drawing by efficient motor program induction, in Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020), 2020.
A. Netanyahu, Shu, T., Katz, B., Barbu, A., and Tenenbaum, J. B., PHASE: PHysically-grounded Abstract Social Eventsfor Machine Social Perception, in Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020, 2020.
M. Nye, Solar-Lezama, A., Tenenbaum, J. B., and Lake, B. M., Learning Compositional Rules via Neural Program Synthesis, in Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020), 2020.
T. D. Ullman and Tenenbaum, J. B., Bayesian Models of Conceptual Development: Learning as Building Models of the World, Annual Review of Developmental Psychology, vol. 2, no. 1, pp. 533 - 558, 2020.
S. Levine, Kleiman-Weiner, M., Schulz, L., Tenenbaum, J. B., and Cushman, F. A., The logic of universalization guides moral judgment, Proceedings of the National Academy of Sciences (PNAS), p. 202014505, 2020.
J. Serrino, Kleiman-Weiner, M., Parkes, D. C., and Tenenbaum, J. B., Finding Friend and Foe in Multi-Agent Games, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.
J. Chu, Gauthier, J., Levy, R., Tenenbaum, J. B., and Schulz, L., Query-guided visual search , in 41st Annual conference of the Cognitive Science Society, Montreal, Québec, Canada, 2019.
K. Ellis, Nye, M., Pu, Y., Sosa, F., Tenenbaum, J. B., and Solar-Lezama, A., Write, Execute, Assess: Program Synthesis with a REPL, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.
C. Han, Mao, J., Gan, C., Tenenbaum, J. B., and Wu, J., Visual Concept-Metaconcept Learning, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.
J. B. Hamrick, Allen, K., Bapst, V., Zhu, T., McKee, K. R., Tenenbaum, J. B., and Battaglia, P., Relational inductive bias for physical construction in humans and machines, In Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci 2018). 2018.
S. Liu, Ullman, T., Tenenbaum, J. B., and Spelke, E. S., Ten-month-old infants infer value from effort, Society for Research in Child Development. 2017.
I. Yildirim and Janner, M., Causal and compositional generative models in online perception, in 39th Annual Conference of the Cognitive Science Society, London, UK, 2017.
I. Yildirim, Janner, M., Belledonne, M., Wallraven, C., Freiwald, W. A., and Tenenbaum, J. B., Causal and compositional generative models in online perception, 39th Annual Meeting of the Cognitive Science Society - COGSCI 2017. London, UK, 2017.
T. Gerstenberg, Zhou, L., Smith, K. A., and Tenenbaum, J. B., Faulty Towers: A counterfactual simulation model of physical support, Proceedings of the 39th Annual Conference of the Cognitive Science Society. 2017.
A. Arsalan Soltani, Huang, H., Wu, J., Kulkarni, T., and Tenenbaum, J. B., Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks, in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, 2017.
Z. Zhang, Wu, J., Li, Q., Huang, Z., Traer, J., McDermott, J. H., Tenenbaum, J. B., and Freeman, W. T., Generative modeling of audible shapes for object perception, in The IEEE International Conference on Computer Vision (ICCV), Venice, Italy, 2017.
J. Wu, Lu, E., Kohli, P., Freeman, W. T., and Tenenbaum, J. B., Learning to See Physics via Visual De-animation, Advances in Neural Information Processing Systems 30. pp. 152–163, 2017.
M. Janner, Wu, J., Kulkarni, T., Yildirim, I., and Tenenbaum, J. B., Self-supervised intrinsic image decomposition., in Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, CA, 2017.
zhoutong zhang, Li, Q., Huang, Z., Wu, J., Tenenbaum, J. B., and Freeman, W. T., Shape and Material from Sound, Advances in Neural Information Processing Systems 30. Long Beach, CA, pp. 1278–1288, 2017.
J. Wu, Wang, Y., Xue, T., Sun, X., Freeman, W. T., and Tenenbaum, J. B., MarrNet: 3D Shape Reconstruction via 2.5D Sketches, Advances in Neural Information Processing Systems 30. Curran Associates, Inc., Long Beach, CA, pp. 540–550, 2017.
J. Jara-Ettinger, Floyd, S., Tenenbaum, J. B., and Schulz, L., Children understand that agents maximize expected utilities., Journal of Experimental Psychology: General, vol. 146, no. 11, pp. 1574 - 1585, 2017.
F. Peres, Smith, K. A., and Tenenbaum, J. B., Rapid Physical Predictions from Convolutional Neural Networks, Neural Information Processing Systems, Intuitive Physics Workshop. 2016.
T. Gerstenberg and Tenenbaum, J. B., Understanding "almost": Empirical and computational studies of near misses, 38th Annual Meeting of the Cognitive Science Society. 38th Annual Meeting of the Cognitive Science Society, 2016.
N. Bramley, Gerstenberg, T., and Tenenbaum, J. B., Natural science: Active learning in dynamic physical microworlds, 38th Annual Meeting of the Cognitive Science Society. 38th Annual Meeting of the Cognitive Science Society, 2016.
T. Gerstenberg and Tenenbaum, J. B., Intuitive theories, in Oxford Handbook of Causal Reasoning, Oxford University Press, 2016.
J. Fischer, Mikhael, J. G., Tenenbaum, J. B., and Kanwisher, N., Functional neuroanatomy of intuitive physical inference, Proceedings of the National Academy of Sciences, vol. 113, no. 34, pp. E5072 - E5081, 2016.
K. Allen, Yildirim, I., and Tenenbaum, J. B., Integrating Identification and Perception: A case study of familiar and unfamiliar face processing, in Proceedings of the Thirty-Eight Annual Conference of the Cognitive Science Society, 2016.
P. Tsividis, Gershman, S. J., Tenenbaum, J. B., and Schulz, L., Information Selection in Noisy Environments with Large Action Spaces, 9th Biennial Conference of the Cognitive Development Society, vol. Columbus, OH. 2015.
J. K. Hartshorne, The causes and consequences explicit in verbs, Language, Cognition and Neuroscience, vol. 30, no. 6, pp. 716-734, 2015.
S. J. Gershman, Tenenbaum, J. B., and Jaekel, F., Discovering hierarchical motion structure, Vision Research, vol. Available online 26 March 2015, 2015.
J. Jara-Ettinger, Not So Innocent: Toddlers’ Inferences About Costs and Culpability, Psychological Science , vol. 26, no. 5, pp. 633-40, 2015.
I. Yildirim, Siegel, M., and Tenenbaum, J. B., Perceiving Fully Occluded Objects with Physical Simulation, in Cognitive Science Conference (CogSci), Pasadena, CA, 2015.
P. Tsividis, Tenenbaum, J. B., and Schulz, L., Hypothesis-Space Constraints in Causal Learning, Annual Meeting of the Cognitive Science Society (CogSci). Pasadena, CA, 2015.
T. Gerstenberg, Goodman, N. D., Lagnado, D. A., and Tenenbaum, J. B., How, whether, why: Causal judgments as counterfactual contrasts, Annual Meeting of the Cognitive Science Society (CogSci). Pasadena, CA, pp. 782-787, 2015.
T. Gerstenberg, Halpern, J. Y., and Tenenbaum, J. B., Responsibility judgments in voting scenarios, Annual Meeting of the Cognitive Science Society (CogSci). Pasadena, CA, pp. 788-793, 2015.