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Filters: Author is Joshua B. Tenenbaum [Clear All Filters]

Conference Paper

Yildirim, I., Siegel, M. & Tenenbaum, J. B. Perceiving Fully Occluded Objects with Physical Simulation. Cognitive Science Conference (CogSci) (2015).

Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception. AAAI-21 (2021).

Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Eventsfor Machine Social Perception. Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020 (2020). at <https://openreview.net/forum?id=_bokm801zhx>

phase_physically_grounded_abstract_social_events_for_machine_social_perception.pdf (2.49 MB)

Kulkarni, T., Kohli, P., Tenenbaum, J. B. & Mansinghka, V. Picture: An Imperative Probabilistic Programming Language for Scene Perception. Computer Vision and Pattern Recognition (2015).

Chu, J., Gauthier, J., Levy, R., Tenenbaum, J. B. & Schulz, L. Query-guided visual search . 41st Annual conference of the Cognitive Science Society (2019).

Janner, M., Wu, J., Kulkarni, T., Yildirim, I. & Tenenbaum, J. B. Self-supervised intrinsic image decomposition. Annual Conference on Neural Information Processing Systems (NIPS) (2017). at <https://papers.nips.cc/paper/7175-self-supervised-intrinsic-image-decomposition>

intrinsicImg_nips_2017.pdf (5.87 MB)

Soltani, A. Arsalan, Huang, H., Wu, J., Kulkarni, T. & Tenenbaum, J. B. Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017). doi:10.1109/CVPR.2017.269

Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks.pdf (2.86 MB)

Mao, J. et al. Temporal and Object Quantification Networks. Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (Zhou, Z. - H.) (2021). doi:10.24963/ijcai.2021/386

0386.pdf (472.5 KB)

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).

Du, Y., Smith, K. A., Ullman, T., Tenenbaum, J. B. & Wu, J. Unsupervised Discovery of 3D Physical Objects. International Conference on Learning Representations (2021). at <https://openreview.net/forum?id=lf7st0bJIA5>

Tejwani, R. et al. Zero-shot linear combinations of grounded social interactions with Linear Social MDPs. Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) (2023).

Conference Post Doc/Student Spotlight Talk

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).

7948-end-to-end-differentiable-physics-for-learning-and-control.pdf (794.17 KB)

Conference Poster

Shu, T. et al. AGENT: A Benchmark for Core Psychological Reasoning. Proceedings of the 38th International Conference on Machine Learning (2021).

Peres, F., Smith, K. A. & Tenenbaum, J. B. Rapid Physical Predictions from Convolutional Neural Networks. Neural Information Processing Systems, Intuitive Physics Workshop (2016). at <http://phys.csail.mit.edu/papers/9.pdf>

Rapid Physical Predictions - NIPS Physics Workshop Poster (1.47 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).