Joshua Tenenbaum

Joshua Tenenbaum
Joshua
Tenenbaum
Research Module Co-Leader
Massachusetts Institute of Technology (MIT)
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
Faculty Profile
Website: 

Current Advisees

Andres Campero Nunez - Graduate Student
Jon Gauthier - Graduate Student
Laila Johnston - Visiting Student
Marta Kryven - Postdoc
John Muchovej - Graduate student
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

Biologically Plausible Implementations of i-theory for feedforward face recognition and object recognition in the ventral stream
Computational Principles of Macaque Face Processing System
Hierarchical motion perception
Human language learning
Inferring "Theory of Mind" from Videos
Intentions and goals in human interactions
Learning and Reasoning in Symbolic Domains
Learning Physics from Dynamic Scenes
Social cognition and the Naïve Utility Calculus
The development of intuitive physics
Towards a Unified Framework for Intuitive Physics
Understanding one's own perceptual abilities

CBMM Publications

X. Puig, Shu, T., Tenenbaum, J. B., and Torralba, A., “NOPA: Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistants”, arXiv, 2023.
R. Tejwani, Kuo, Y. - L., Shu, T., Stankovits, B., Gutfreund, D., Tenenbaum, J. B., Katz, B., and Barbu, A., “Zero-shot linear combinations of grounded social interactions with Linear Social MDPs”, in Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.
T. P. O'Connell, Bonnen, T., Friedman, Y., Tewari, A., Tenenbaum, J. B., Sitzmann, V., and Kanwisher, N., “Approaching human 3D shape perception with neurally mappable models”, arXiv, 2023.
U. Singhal, Cheung, B., Chandra, K., Ragan-Kelley, J., Tenenbaum, J. B., Poggio, T., and Yu, S. X., “How to Guess a Gradient”, arXiv, 2023.
R. Tejwani, Kuo, Y. - L., Shu, T., Stankovits, B., Gutfreund, D., Tenenbaum, J. B., Katz, B., and Barbu, A., “Incorporating Rich Social Interactions Into MDPs”. 2022.
L. Zhou, Smith, K., Tenenbaum, J. B., and Gerstenberg, T., “Mental Jenga: A counterfactual simulation model of causal judgments about physical support”, PsyArXiv, 2022.
A. Netanyahu, Shu, T., Katz, B., Barbu, A., and Tenenbaum, J. B., “PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception”, in AAAI-21, 2021.
A. Netanyahu, Shu, T., Katz, B., Barbu, A., and Tenenbaum, J. B., “PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception”. 2021.
S. Dae Houlihan, Tenenbaum, J. B., and Saxe, R., The Neural Basis of Mentalizing: Linking Models of Theory of Mind and Measures of Human Brain Activity. Cham: Springer International Publishing, 2021, pp. 209 - 235.
F. A. Sosa, Ullman, T., Tenenbaum, J. B., Gershman, S. J., and Gerstenberg, T., “Moral dynamics: Grounding moral judgment in intuitive physics and intuitive psychology”, Cognition, vol. 217, p. 104890, 2021.
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.
T. Shu, Bhandwaldar, A., Gan, C., Smith, K. A., Liu, S., Gutfreund, D., Spelke, E. S., Tenenbaum, J. B., and Ullman, T. D., “ AGENT: A Benchmark for Core Psychological Reasoning”, Proceedings of the 38th International Conference on Machine Learning. 2021.
K. Allen, Smith, K. A., Bird, L., Tenenbaum, J. B., Makin, T., and Cowie, D., “Meta-strategy learning in physical problem solving: the effect of embodied experience”, bioRxiv, 2021.
M. Kryven, Ullman, T. D., Cowan, W., and Tenenbaum, J. B., “Plans or Outcomes: How Do We Attribute Intelligence to Others?”, Cognitive Science, vol. 45, no. 9, 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.
M. Schrimpf, Blank, I. Asher, Tuckute, G., Kauf, C., Hosseini, E. A., Kanwisher, N., Tenenbaum, J. B., and Fedorenko, E., “The neural architecture of language: Integrative modeling converges on predictive processing”, Proceedings of the National Academy of Sciences, vol. 118, no. 45, p. e2105646118, 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. Yildirim, Belledonne, M., Freiwald, W. A., and Tenenbaum, J. B., “Efficient inverse graphics in biological face processing”, Science Advances, vol. 6, no. 10, p. eaax5979, 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.
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.
J. Schwartz, Alter, S., DiCarlo, J. J., McDermott, J. H., Tenenbaum, J. B., Yamins, D. L. K., Gutfreund, D., Gan, C., Traer, J., Kubilius, J., Schrimpf, M., Bhandwaldar, A., De Freitas, J., Mrowca, D., Lingelbach, M., Sano, M., Bear, D., Kim, K., Haber, N., and Fan, C., “ThreeDWorld (TDW): A High-Fidelity, Multi-Modal Platform for Interactive Physical Simulation”. 2020.
C. Gen, Schwartz, J., Alter, S., Schrimpf, M., Traer, J., De Freitas, J., Kubilius, J., Bhandwaldar, A., Haber, N., Sano, M., Kim, K., Wang, E., Mrowca, D., Lingelbach, M., Curtis, A., Feigleis, K., Bear, D., Gutfreund, D., Cox, D., DiCarlo, J. J., McDermott, J. H., Tenenbaum, J. B., and Yamins, D. L. K., “ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation”, arXiv, 2020.
M. Sheskin, Scott, K., Mills, C. M., Bergelson, E., Bonawitz, E., Spelke, E. S., Fei-Fei, L., Keil, F. C., Gweon, H., Tenenbaum, J. B., Jara-Ettinger, J., Adolph, K. E., Rhodes, M., Frank, M. C., Mehr, S. A., and Schulz, L., “Online Developmental Science to Foster Innovation, Access, and Impact”, Trends in Cognitive Sciences, vol. 24, no. 9, pp. 675 - 678, 2020.
K. Allen, Smith, K. A., and Tenenbaum, J. B., “Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning”, Proceedings of the National Academy of Sciences, p. 201912341, 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.
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.
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.
I. Yildirim, Wu, J., Kanwisher, N., and Tenenbaum, J. B., “An integrative computational architecture for object-driven cortex”, Current Opinion in Neurobiology, vol. 55, pp. 73 - 81, 2019.
N. Fazeli, Oller, M., Wu, J., Wu, Z., Tenenbaum, J. B., and Rodriguez, A., “See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion”, Science Robotics, vol. 4, no. 26, p. eaav3123, 2019.
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.
T. D. Ullman, Kosoy, E., Yildirim, I., Soltani, A. Arsalan, Siegel, M., Tenenbaum, J. B., and Spelke, E. S., “Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects”, Cognitive Science Society. Montreal, 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.
M. Kryven, Niemi, L., Paul, L., and Tenenbaum, J. B., “Choosing a Transformative Experience ”, Cognitive Sciences Society. 2019.
M. Kryven, Scholl, B., and Tenenbaum, J. B., “ Does intuitive inference of physical stability interruptattention?”, Cognitive Sciences Society. 2019.
K. A. Smith, Mei, L., Yao, S., Wu, J., Spelke, E. S., Tenenbaum, J. B., and Ullman, T. D., “Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations”, 33rd Conference on 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.
A. Barbu, Mayo, D., Alverio, J., Luo, W., Wang, C., Gutfreund, D., Tenenbaum, J. B., and Katz, B., “ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, 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.
S. Schwettmann, Tenenbaum, J. B., and Kanwisher, N., “Invariant representations of mass in the human brain”, eLife, vol. 8, 2019.
Fde Avila Belbute-Peres, Smith, K. A., Allen, K., Tenenbaum, J. B., and Kolter, Z., “End-to-end differentiable physics for learning and control”, Advances in Neural Information Processing Systems 31 (NIPS 2018). 2018.
Y. Wu, Baker, C., Tenenbaum, J. B., and Schulz, L., “Rational inference of beliefs and desires from emotional expressions”, Cognitive Science, vol. 42, no. 3, 2018.
D. Harari, Tenenbaum, J. B., and Ullman, S., “Discovery and usage of joint attention in images”, arXiv.org, 2018.
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.
M. Toussaint, Allen, K., Smith, K. A., and Tenenbaum, J. B., “Differentiable physics and stable modes for tool-use and manipulation planning”, Robotics: Science and Systems 2018. 2018.
T. Gerstenberg, Ullman, T. D., Nagel, J., Kleiman-Weiner, M., Lagnado, D. A., and Tenenbaum, J. B., “Lucky or clever? From changed expectations to attributions of responsibility”, Cognition, 2018.
T. D. Ullman, Stuhlmüller, A., Goodman, N. D., and Tenenbaum, J. B., “Learning physical parameters from dynamic scenes.”, Cognitive Psychology, vol. 104, pp. 57-82, 2018.
T. Gerstenberg, Peterson, M. F., Goodman, N. D., Lagnado, D. A., and Tenenbaum, J. B., “Eye-Tracking Causality”, Psychological Science, 2017.
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.
P. Tsividis, Pouncy, T., Xu, J. L., Tenenbaum, J. B., and Gershman, S. J., “Human Learning in Atari”, in AAAI Spring Symposium Series, 2017.
T. Ullman, Tenenbaum, J. B., and Spelke, E. S., “Critical Cues in Early Physical Reasoning”, SRCD. Austin, TX, 2017.
S. Liu, Ullman, T., Tenenbaum, J. B., and Spelke, E. S., “Ten-month-old infants infer value from effort”, SRCD. Austin, TX, 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.
C. Baker, Jara-Ettinger, J., Saxe, R., and Tenenbaum, J. B., “Rational quantitative attribution of beliefs, desires, and percepts in human mentalizing”, Nature Human Behavior, vol. 1, no. 0064, 2017.
R. Magid, Yan, P., Siegel, M., Tenenbaum, J. B., and Schulz, L., “Changing minds: Children’s inferences about third party belief revision”, Developmental Science, p. e12553, 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.
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.
I. Yildirim, Gerstenberg, T., Saeed, B., Toussant, M., and 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.
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.
T. D. Ullman, Spelke, E. S., Battaglia, P., and Tenenbaum, J. B., “Mind Games: Game Engines as an Architecture for Intuitive Physics”, Trends in Cognitive Science, vol. 21, no. 9, pp. 649 - 665, 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.
T. Gerstenberg, Peterson, M. F., Goodman, N. D., Lagnado, D. A., and Tenenbaum, J. B., “Eye-Tracking Causality”, Psychological Science, vol. 73, 2017.
S. Liu, Ullman, T. D., Tenenbaum, J. B., and Spelke, E. S., “Ten-month-old infants infer the value of goals from the costs of actions”, Science, vol. 358, pp. 1038-1041, 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. 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.
E. Schulz, Tenenbaum, J. B., Duvenaud, D., Speekenbrink, M., and Gershman, S. J., “Compositional inductive biases in function learning.”, Cogn Psychol, vol. 99, pp. 44-79, 2017.
B. M. Lake, Ullman, T. D., Tenenbaum, J. B., and Gershman, S. J., “Building machines that learn and think like people.”, Behavioral and Brain Sciences, vol. 40, p. e253, 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.
J. Jara-Ettinger, Gweon, H., Schulz, L., and Tenenbaum, J. B., “The naive utility calculus: computational principles underlying social cognition”, Trends Cogn Sci., 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.
M. Kleiman-Weiner, Ho, M. K., Austerweil, J. L., L, L. Michael, and Tenenbaum, J. B., “Coordinate to cooperate or compete: abstract goals and joint intentions in social interaction”, in Proceedings of the 38th Annual Conference 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.
F. Peres, Smith, K. A., and Tenenbaum, J. B., “Rapid Physical Predictions from Convolutional Neural Networks”, Neural Information Processing Systems, Intuitive Physics Workshop. 2016.
P. Krafft, Baker, C., Pentland, A., and Tenenbaum, J. B., “Modeling Human Ad Hoc Coordination”, AAAI. 2016.
R. Nakahashi, Baker, C., and Tenenbaum, J. B., “Modeling human understanding of complex intentional action with a Bayesian nonparametric subgoal model”, in AAAI, 2016.
T. Gerstenberg and Tenenbaum, J. B., “Intuitive theories”, in Oxford Handbook of Causal Reasoning, Oxford University Press, 2016.
B. M. Lake, Ullman, T., Tenenbaum, J. B., and Gershman, S. J., “Building machines that learn and think like people”. 2016.
E. Schulz, Tenenbaum, J. B., Duvenaud, D., Speekenbrink, M., and Gershman, S. J., “Probing the compositionality of intuitive functions”. 2016.
T. Ullman, Tenenbaum, J. B., and Spelke, E. S., “Effort as a bridging concept across action and action understanding: Weight and Physical Effort in Predictions of Efficiency in Other Agents”, in International Conference on Infant Studies (ICIS) , New Orleans, Louisiana, 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.
D. Harari, Gao, T., Kanwisher, N., Tenenbaum, J. B., and Ullman, S., “Measuring and modeling the perception of natural and unconstrained gaze in humans and machines”. 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. Wu, Yildirim, I., Lim, J. J., Freeman, W. T., and Tenenbaum, J. B., “Galileo: Perceiving physical object properties by integrating a physics engine with deep learning.”, in NIPS 2015, Montréal, Canada, 2015.
T. Kulkarni, Kohli, P., Tenenbaum, J. B., and Mansinghka, V., “Picture: An Imperative Probabilistic Programming Language for Scene Perception”, in Computer Vision and Pattern Recognition, 2015.
I. Yildirim, Kulkarni, T., Freiwald, W. A., and Tenenbaum, J. B., “Efficient and robust analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations”, in Annual Conference of the Cognitive Science Society, 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.
S. J. Gershman, Horvitz, E. J., and Tenenbaum, J. B., “Computational rationality: A converging paradigm for intelligence in brains, minds, and machines”, Science, vol. 349, no. 6245, pp. 273-278, 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.
J. Jara-Ettinger, Gweon, H., Tenenbaum, J. B., and Schulz, L., “Children’s understanding of the costs and rewards underlying rational action”, Cognition, vol. 140, pp. 14–23, 2015.
I. Yildirim, Siegel, M., and Tenenbaum, J. B., “Perceiving Fully Occluded Objects with Physical Simulation”, in Cognitive Science Conference (CogSci), Pasadena, CA, 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.
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.
B. M. Lake, Salakhutdinov, R., and Tenenbaum, J. B., “Human-level concept learning through probabilistic program induction”, Science, vol. 350, no. 6266, pp. 1332-1338 , 2015.
I. Yildirim, Kulkarni, T., Freiwald, W. A., and Tenenbaum, J. B., “Explaining Monkey Face Patch System as Efficient Analysis-by-Synthesis”. 2014.
N. D. Goodman, Tenenbaum, J. B., and Gerstenberg, T., “Concepts in a Probabilistic Language of Thought.”. 2014.
T. Gao, Harari, D., Tenenbaum, J. B., and Ullman, S., “When Computer Vision Gazes at Cognition.”. 2014.