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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).
Invariant representations of mass in the human brain. eLife 8, (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)
Building machines that learn and think like people. Behavioral and Brain Sciences 40, e253 (2017).
Causal and compositional generative models in online perception. 39th Annual Conference of the Cognitive Science Society ( ) (2017). yildirim_janner_2_1.pdf (6.88 MB)
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>
Changing minds: Children’s inferences about third party belief revision. Developmental Science e12553 (2017). doi:10.1111/desc.12553 Changing Minds_MagidYanSiegelTenenbaumSchulz_in press.pdf (915.8 KB)
Children understand that agents maximize expected utilities. Journal of Experimental Psychology: General 146, 1574 - 1585 (2017). ExpectedUtilities_Final.pdf (950.09 KB)
Compositional inductive biases in function learning. Cogn Psychol 99, 44-79 (2017).