All Publications

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.PDF icon intrinsicImg_nips_2017.pdf (5.87 MB)
CBMM Funded
A. Tacchetti, Isik, L., and Poggio, T., “Invariant recognition drives neural representations of action sequences”, PLOS Computational Biology, vol. 13, no. 12, p. e1005859, 2017.PDF icon journal.pcbi_.1005859.pdf (9.24 MB)
CBMM Funded
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.PDF icon Learning to See Physics via Visual De-animation (1.11 MB)
CBMM Funded
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.PDF icon MarrNet: 3D Shape Reconstruction via 2.5D Sketches (6.25 MB)
CBMM Funded
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.
CBMM Funded
L. Isik, Tacchetti, A., and Poggio, T., “A fast, invariant representation for human action in the visual system.”, J Neurophysiol, p. jn.00642.2017, 2017.PDF icon Author's last draft (695.63 KB)
CBMM Funded
T. Liang, Poggio, T., Rakhlin, A., and Stokes, J., “Fisher-Rao Metric, Geometry, and Complexity of Neural Networks”, 2017.PDF icon 1711.01530.pdf (966.99 KB)
CBMM Related
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.PDF icon ivc_full_preprint_withsm.pdf (1.6 MB)
CBMM Funded
E. Meyers, Riley, M., Qi, X. - L., and Constantinidis, C., “Differences in dynamic and static coding within different subdivision of the prefrontal cortex”, Society for Neuroscience's Annual Meeting - SfN 2017. Washington, DC, 2017.
CBMM Funded
A. Tacchetti, Isik, L., and Poggio, T., “Invariant action recognition dataset”. 2017.
CBMM Funded
CBMM Memo No.
080
W. Shen, Wang, B., Jiang, Y., Wang, Y., and Yuille, A., “Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection”. 2017.PDF icon CBMM-Memo-080.pdf (2.51 MB)
CBMM Funded
CBMM Memo No.
070
Q. Liao and Poggio, T., “Object-Oriented Deep Learning”. 2017.PDF icon CBMM-Memo-070.pdf (963.54 KB)
CBMM Funded
T. Gerstenberg, Peterson, M. F., Goodman, N. D., Lagnado, D. A., and Tenenbaum, J. B., “Eye-Tracking Causality”, Psychological Science, vol. 73, 2017.
CBMM Funded
L. Isik, Koldewyn, K., Beeler, D., and Kanwisher, N., “Perceiving social interactions in the posterior superior temporal sulcus”, Proceedings of the National Academy of Sciences, vol. 114, no. 43, 2017.
CBMM Funded
R. Magid and Schulz, L., “Moral alchemy: How love changes norms”, Cognition, vol. 167, pp. 135 -150, 2017.PDF icon Moral Alchemy_Magid&Schulz.pdf (627.46 KB)
CBMM Related
E. Meyers, Liang, A., Katsuki, F., and Constantinidis, C., “Differential Processing of Isolated Object and Multi-item Pop-Out Displays in LIP and PFC.”, Cerebral Cortex, 2017.
CBMM Funded
R. Saxe and Houlihan, S. Dae, “Formalizing emotion concepts within a Bayesian model of theory of mind”, Current Option in Psychology, vol. 17, pp. 15-21, 2017.PDF icon 1-s2.0-S2352250X17300283-main.pdf (613.77 KB)
CBMM Funded
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.
CBMM Related
CBMM Memo No.
078
J. Wang, Xie, C., Zhang, Z., Zhu, J., Xie, L., and Yuille, A., “Detecting Semantic Parts on Partially Occluded Objects”. 2017.PDF icon CBMM-Memo-078.pdf (1.74 MB)
CBMM Funded
M. J. Arcaro, Schade, P. F., Vincent, J. L., Ponce, C. R., and Livingstone, M. S., “Seeing faces is necessary for face-domain formation”, Nature Neuroscience, vol. 5631628, 2017.
CBMM Related
H. Lin and Tegmark, M., “Why does deep and cheap learning work so well?”, Journal of Statistical Physics, vol. 168, no. 6, pp. 1223–1247, 2017.PDF icon 1608.08225.pdf (2.14 MB)
CBMM Related
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.PDF icon Preprint submitted to Trends in Cognitive Science (17.64 MB)
CBMM Funded
J. Wang, Xie, C., Zhang, Z., Zhu, J., Xie, L., and Yuille, A., “Detecting Semantic Parts on Partially Occluded Objects”, in British Machine Vision Conference (BMVC), London, UK, 2017.
CBMM Funded
L. Jing, Shen, Y., Dubček, T., Peurifoi, J., Skirlo, S., LeCun, Y., Tegmark, M., and Soljačić, M., “Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN”, 34th International Conference on Machine Learning, vol. 70. pp. 1733-1741 , 2017.PDF icon 1612.05231.pdf (2.3 MB)
CBMM Related
S. M. Landi and Freiwald, W. A., “Two areas for familiar face recognition in the primate brain”, Science, vol. 357, no. 6351, pp. 591 - 595, 2017.PDF icon 591.full_.pdf (928.29 KB)
CBMM Funded

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