All Publications

2016

T. Gerstenberg and Tenenbaum, J. B., “Intuitive theories”, in Oxford Handbook of Causal Reasoning, Oxford University Press, 2016.PDF icon Intuitive Theories (Gerstenberg, Tenenbaum, 2016.pdf (6.06 MB)
CBMM Funded
F. S. Kamps, Julian, J. B., Kubilius, J., Kanwisher, N., and Dilks, D. D., “The occipital place area represents the local elements of scenes”, NeuroImage, vol. 132, pp. 417 - 424, 2016.
CBMM Funded
P. Krafft, Baker, C., Pentland, A., and Tenenbaum, J. B., “Modeling Human Ad Hoc Coordination”, AAAI. 2016.PDF icon krafft_aaai2016.pdf (247.58 KB)
CBMM Funded
R. Lafer-Sousa, Conway, B. R., and Kanwisher, N., “Color-Biased Regions of the Ventral Visual Pathway Lie between Face- and Place-Selective Regions in Humans, as in Macaques”, Journal of Neuroscience, vol. 36, no. 5, pp. 1682 - 1697, 2016.
CBMM Funded
W. Mlynarski and McDermott, J. H., “Learning mid-level codes for natural sounds”, Computational and Systems Neuroscience (Cosyne) 2016. Salt Lake City, UT, 2016.PDF icon Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)
CBMM Funded
R. Nakahashi, Baker, C., and Tenenbaum, J. B., “Modeling human understanding of complex intentional action with a Bayesian nonparametric subgoal model”, in AAAI, 2016.PDF icon nakahashi_aaai2016.pdf (1.74 MB)
CBMM Funded
H. Tang, Yu, H. Y., Chou, C. C., Crone, N. E., Madsen, J., Anderson, W. S., and Kreiman, G., “Cascade of neural processing orchestrates cognitive control in human frontal cortex”, eLIFE, 2016.PDF icon Manuscript  (1.83 MB)
CBMM Funded
CBMM Memo No.
044
Y. Luo, Boix, X., Roig, G., Poggio, T., and Zhao, Q., “Foveation-based Mechanisms Alleviate Adversarial Examples”. 2016.PDF icon cbmm_memo_044.pdf (11.48 MB)
CBMM Funded
CBMM Memo No.
043
O. Morère, Veillard, A., Lin, J., Petta, J., Chandrasekhar, V., and Poggio, T., “Group Invariant Deep Representations for Image Instance Retrieval”. 2016.PDF icon CBMM-Memo-043.pdf (2.66 MB)
CBMM Funded
CBMM Memo No.
042
L. Isik, Tacchetti, A., and Poggio, T., “Fast, invariant representation for human action in the visual system”. 2016.PDF icon CBMM Memo 042 (3.03 MB)
CBMM Funded
Y. Berzak, Barbu, A., Harari, D., Katz, B., and Ullman, S., “Language and Vision Ambiguities (LAVA) Corpus”. 2016.PDF icon D15-1172.pdf (2.42 MB)
CBMM Funded
G. Kreiman, “Neural Information Processing Systems (NIPS) 2015 Review”. 2016.PDF icon Read the Views & Review article by Gabriel Kreiman (443.87 KB)
S. Liu and Spelke, E. S., “Continuous representations of action efficiency in infancy”, CEU Conference on Cognitive Development (BCCCD16). 2016.
CBMM Funded
E. Meyers, “Review of the CBMM workshop on the Turing++ Question: 'who is there?'”. 2016.PDF icon Review of the CBMM workshop on the Turing++ Question- 'who is there?' .pdf (555.71 KB)
H. Mhaskar and Poggio, T., “Deep vs. shallow networks: An approximation theory perspective”, Analysis and Applications, vol. 14, no. 06, pp. 829 - 848, 2016.
CBMM Funded
CBMM Memo No.
045
H. Mhaskar, Liao, Q., and Poggio, T., “Learning Functions: When Is Deep Better Than Shallow”. 2016.
CBMM Funded
F. Bach and Poggio, T., “Introduction Special issue: Deep learning”, Information and Inference, vol. 5, pp. 103-104, 2016.
CBMM Funded
L. Bergen, Levy, R., and Goodman, N. D., “Pragmatic Reasoning through Semantic Inference”, Semantics and Pragmatics, vol. Vol 9 (2016) , 2016.PDF icon BergenLevyGoodman2015.pdf (1.12 MB)
CBMM Related
N. Bramley, Gerstenberg, T., and Tenenbaum, J. B., “Natural science: Active learning in dynamic physical microworlds”, 38th Annual Meeting of the Cognitive Science Society. 38th Annual Meeting of the Cognitive Science Society, 2016.PDF icon Natural Science (Bramley, Gerstenberg, Tenenbaum, 2016).pdf (5.39 MB)
CBMM Funded
N. Dehghani, “Dynamic balance of excitation and inhibition in human and monkey neocortex”, Nature Scientific Reports, 2016.PDF icon BalanceExcitationInhibition.pdf (2.1 MB)
CBMM Related
M. R. Dillon and Spelke, E. S., “Young Children’s Use of Surface and Object Information in Drawings of Everyday Scenes”, Child Development, 2016.
CBMM Related
T. Gerstenberg and Tenenbaum, J. B., “Understanding "almost": Empirical and computational studies of near misses”, 38th Annual Meeting of the Cognitive Science Society. 38th Annual Meeting of the Cognitive Science Society, 2016.PDF icon Understanding almost (Gerstenberg, Tenenbaum, 2016).pdf (4.08 MB)
CBMM Funded
C. Gómez-Laberge, Smolyanskaya, A., Nassi, J. J., Kreiman, G., and Born, R. T., “Bottom-up and Top-down Input Augment the Variability of Cortical Neurons.”, Neuron, vol. 91(3), pp. 540-547, 2016.
CBMM Funded
J. K. Hartshorne, “VerbCorner: Testing theories of argument structure through crowdsourcing”, Workshop on Events in Language. 2016.PDF icon VerbCorner_EventsInLanguage.pdf (1.14 MB)
CBMM Related
J. Jara-Ettinger, Gweon, H., Schulz, L., and Tenenbaum, J. B., “The naive utility calculus: computational principles underlying social cognition”, Trends Cogn Sci., 2016.
CBMM Funded

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