All Publications

2017

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. D., “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
R. Paul, Barbu, A., Felshin, S., Katz, B., and Roy, N., “Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context”, in Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia, 2017.
CBMM Funded
G. Kreiman, “A null model for cortical representations with grandmothers galore”, Language, Cognition and Neuroscience, pp. 274 - 285, 2017.
CBMM Funded
T. Gerstenberg, Zhou, L., Smith, K. A., and Tenenbaum, J. B., “Faulty Towers: A counterfactual simulation model of physical support”, Proceedings of the 39th Annual Conference of the Cognitive Science Society. 2017.PDF icon Faulty Towers A counterfactual simulation model of physical support, Gerstenberg et al., 2017.pdf (8.75 MB)
CBMM Funded
G. Manek, Lin, J., Chandrasekhar, V., Duan, L., Giduthuri, S., Li, X., and Poggio, T., “Pruning Convolutional Neural Networks for Image Instance Retrieval”, 2017.PDF icon 1707.05455.pdf (143.46 KB)
CBMM Related
H. Penagos, Varela, C., and Wilson, M. A., “Oscillations, neural computations and learning during wake and sleep”, Current Opinion in Neurobiology, vol. 44C, no. June 2017, 2017.
CBMM Funded
A. Arsalan Soltani, Huang, H., Wu, J., Kulkarni, T., and Tenenbaum, J. B., “Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks”, in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, 2017.PDF icon Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks.pdf (2.86 MB)
CBMM Related
S. Stephan, Willemsen, P., and Gerstenberg, T., “Marbles in inaction: Counterfactual simulation and causation by omission”, Proceedings of the 39th Annual Conference of the Cognitive Science Society. 2017.PDF icon Marbles in Inaction Counterfactual Simulation and Causation by Omission, Stephan, Willemsen, Gerstenberg, 2017.pdf (1.46 MB)
CBMM Funded
I. Yildirim, Gerstenberg, T., Saeed, B., Toussant, M., and Tenenbaum, J. B., “Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints”, Proceedings of the 39th Annual Conference of the Cognitive Science Society. 2017.PDF icon Physical problem solving Joint planning with symbolic, geometric, and dynamic constraints, Yildirim et al., 2017.pdf (2.46 MB)
CBMM Funded
I. Yildirim, Janner, M., Belledonne, M., Wallraven, C., Freiwald, W. A., and Tenenbaum, J. B., “Causal and compositional generative models in online perception”, 39th Annual Meeting of the Cognitive Science Society - COGSCI 2017. London, UK, 2017.
CBMM Related
CBMM Memo No.
069
A. Volokitin, Roig, G., and Poggio, T., “Do Deep Neural Networks Suffer from Crowding?”. 2017.PDF icon CBMM-Memo-069.pdf (6.47 MB)
CBMM Funded
CBMM Memo No.
068
B. Subirana, Bagiati, A., and Sarma, S., “On the Forgetting of College Academics: at "Ebbinghaus Speed"?”. 2017.PDF icon CBMM Memo 068-On Forgetting - June 18th 2017 v2.pdf (713.7 KB)
CBMM Funded
A. Volokitin and Roig, G., “Do Deep Neural Networks Suffer from Crowding? [code]”. 2017.
CBMM Funded
CBMM Memo No.
063
F. Anselmi, Evangelopoulos, G., Rosasco, L., and Poggio, T., “Symmetry Regularization”. 2017.PDF icon CBMM-Memo-063.pdf (6.1 MB)
CBMM Funded

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