Publication
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Filters: Author is Joshua B. Tenenbaum [Clear All Filters]
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)
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. arXiv (2020). at <https://arxiv.org/abs/2007.04954> 2007.04954.pdf (7.06 MB)
ThreeDWorld (TDW): A High-Fidelity, Multi-Modal Platform for Interactive Physical Simulation. (2020). at <http://www.threedworld.org/>
Toward human-like object naming in artificial neural systems . International Conference on Learning Representations (ICLR 2020), Bridging AI and Cognitive Science workshop (2020).
Choosing a Transformative Experience . Cognitive Sciences Society (2019).
Does intuitive inference of physical stability interruptattention?. Cognitive Sciences Society (2019).
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)
Finding Friend and Foe in Multi-Agent Games. Neural Information Processing Systems (NeurIPS 2019) (2019). Max KW paper.pdf (928.96 KB)
An integrative computational architecture for object-driven cortex. Current Opinion in Neurobiology 55, 73 - 81 (2019).
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)
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)
Query-guided visual search . 41st Annual conference of the Cognitive Science Society (2019).
See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion. Science Robotics 4, eaav3123 (2019).
Visual Concept-Metaconcept Learning. Neural Information Processing Systems (NeurIPS 2019) (2019). 8745-visual-concept-metaconcept-learning.pdf (1.92 MB)
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)
Differentiable physics and stable modes for tool-use and manipulation planning. Robotics: Science and Systems 2018 (2018). ToussaintEtAl_DiffPhysStable.pdf (1.97 MB)
Discovery and usage of joint attention in images. arXiv.org (2018). at <https://arxiv.org/abs/1804.04604> 1804.04604v1.pdf (488.85 KB)
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)
Learning physical parameters from dynamic scenes. Cognitive Psychology 104, 57-82 (2018). T-Ullman-etal_CogPsych_LearningPhysicalParametersFromDynamicScenes.pdf (3.15 MB)
Lucky or clever? From changed expectations to attributions of responsibility. Cognition (2018).
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)
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)