All Publications

2016

CBMM Memo No.
047
Q. Liao and Poggio, T., “Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex”. 2016.PDF icon CBMM Memo No. 047 (1.29 MB)
CBMM Funded
CBMM Memo No.
046
B. M. Lake, Ullman, T., Tenenbaum, J. B., and Gershman, S. J., “Building machines that learn and think like people”. 2016.PDF icon machines_that_think.pdf (3.45 MB)
CBMM Funded
T. Poggio, “Deep Learning: mathematics and neuroscience”. 2016.PDF icon Deep Learning- mathematics and neuroscience.pdf (1.25 MB)
O. Morère, Veillard, A., Chandrasekhar, V., and Poggio, T., “Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval”, arXiv.org, 2016.PDF icon 1603.04595.pdf (2.9 MB)
CBMM Related
T. Poggio and Meyers, E., “Turing++ Questions: A Test for the Science of (Human) Intelligence.”, AI Magazine, vol. 37 , no. 1, pp. 73-77, 2016.PDF icon Turing_Plus_Questions.pdf (424.91 KB)
CBMM Funded
C. Tan and Poggio, T., “Neural Tuning Size in a Model of Primate Visual Processing Accounts for Three Key Markers of Holistic Face Processing”, Public Library of Science | PLoS ONE , vol. 1(3): e0150980, 2016.PDF icon journal.pone_.0150980.PDF (384.15 KB)
CBMM Funded
S. Ullman, Assif, L., Fetaya, E., and Harari, D., “Atoms of recognition in human and computer vision”, PNAS , vol. 113, no. 10, pp. 2744–2749, 2016.PDF icon mirc_author_manuscript_with_figures_and_SI-2.pdf (1.65 MB)
CBMM Funded
P. Henry Winston, “Marvin L. Minsky (1927–2016) Scientist and inventor was a visionary founder of AI”. 2016.PDF icon Marvin L. Minsky (1927–2016) Scientist and inventor was a visionary founder of AI.pdf (559.42 KB)
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

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