Publication

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2020
Gen, C. et al. ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. arXiv (2020). at <https://arxiv.org/abs/2007.04954>PDF icon 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>PDF icon 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).PDF icon 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/>PDF icon 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).PDF icon 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).PDF icon 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).PDF icon 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).PDF icon 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>PDF icon 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).PDF icon 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).PDF icon 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).PDF icon 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).PDF icon 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).
Yildirim, I. et al. Causal and compositional generative models in online perception. 39th Annual Meeting of the Cognitive Science Society - COGSCI 2017 (2017). at <https://mindmodeling.org/cogsci2017/papers/0266/index.html>
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).PDF icon yildirim_janner_2_1.pdf (6.88 MB)

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