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2016
Functional neuroanatomy of intuitive physical inference. (2016).
Spokes, A. C. & Spelke, E. S. The Functions of Infants’ Social Categorization: Early Reasoning about Affiliation and Social Networks. International Conference on Infant Studies (ICIS) (2016).
Mao, J. et al. Generation and Comprehension of Unambiguous Object Descriptions. The Conference on Computer Vision and Pattern Recognition (CVPR) (2016). at <https://github.com/ mjhucla/Google_Refexp_toolbox>PDF icon object_description_cbmm.pdf (2.21 MB)
Morère, O. et al. Group Invariant Deep Representations for Image Instance Retrieval. (2016).PDF icon CBMM-Memo-043.pdf (2.66 MB)
Le Van Quyen, M. et al. High-frequency oscillations in human and monkey neocortex during the wake–sleep cycle. Proceedings of the National Academy of Sciences (2016). doi:10.1073/pnas.1523583113PDF icon BetaGammaSleepAwakeFull.pdf (3.68 MB)
Nickel, M., Rosasco, L. & Poggio, T. Holographic Embeddings of Knowledge Graphs. Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) (2016).PDF icon 1510.04935v2.pdf (360.65 KB)
Liao, Q., Leibo, J. Z. & Poggio, T. How Important Is Weight Symmetry in Backpropagation?. Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) (Association for the Advancement of Artificial Intelligence, 2016).PDF icon liao-leibo-poggio.pdf (191.91 KB)
Liao, Q., Leibo, J. Z. & Poggio, T. How Important Is Weight Symmetry in Backpropagation?. Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) (2016). at <https://cbmm.mit.edu/sites/default/files/publications/liao-leibo-poggio.pdf>
Spokes, A. C. How Infants Reason About Affective States and Social Interactions. International Conference on Infant Studies (ICIS) (2016).
Lifshitz, I., Fetaya, E. & Ullman, S. Human Pose Estimation Using Deep Consensus Voting. ECCV 2016 (2016).PDF icon 1603.08212.pdf (6.05 MB)
Tegmark, M. Improved Measures of Integrated Information. PLOS Computational Biology (2016). doi:10.1371/journal.pcbi.100512310.1371PDF icon 1601.02626.pdf (3.49 MB)
Peterson, M. F., Lin, J., Zaun, I. & Kanwisher, N. Individual Differences in Face Looking Behavior Generalize from the Lab to the World. Journal of Vision 16, (2016).PDF icon Real World Face Fixations, Journal of Vision article, 2016 (20.25 MB)
Peterson, M. F., Lin, J., Zaun, I. & Kanwisher, N. Individual differences in face-looking behavior generalize from the lab to the world. Journal of Vision (2016).
Dehaene-Lambertz, G. & Spelke, E. S. The infancy of the human brain. (2016). doi:http://dx.doi.org/10.1016/j.neuron.2015.09.026PDF icon CBMM-Memo-053.pdf (1.51 MB)
Inferring mass in complex scenes by mental simulation. (2016).
Allen, K., Yildirim, I. & Tenenbaum, J. B. Integrating Identification and Perception: A case study of familiar and unfamiliar face processing. Proceedings of the Thirty-Eight Annual Conference of the Cognitive Science Society (2016).PDF icon allen_5_13.pdf (2.13 MB)
Bach, F. & Poggio, T. Introduction Special issue: Deep learning. Information and Inference 5, 103-104 (2016).
Gerstenberg, T. & Tenenbaum, J. B. Oxford Handbook of Causal Reasoning (Oxford University Press, 2016).PDF icon Intuitive Theories (Gerstenberg, Tenenbaum, 2016.pdf (6.06 MB)
Anselmi, F., Rosasco, L. & Poggio, T. On invariance and selectivity in representation learning. Information and Inference: A Journal of the IMA iaw009 (2016). doi:10.1093/imaiai/iaw009PDF icon imaiai.iaw009.full_.pdf (267.87 KB)
Wu, Y., Muentener, P. & Schulz, L. The invisible hand: Toddlers connect probabilistic events with agentive causes. Cognitive Science 40, 23 (2016).PDF icon Wu_Muentener_Schulz_2016_InvisibleHand.pdf (307.21 KB)
Rockmore, D. Is it time for a presidential technoethics commission. (2016). at <https://theconversation.com/is-it-time-for-a-presidential-technoethics-commission-58846>PDF icon rockmore - Is it time for a presidential technoethics commission.pdf (280.2 KB)
Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Language and Vision Ambiguities (LAVA) Corpus. (2016). at <http://web.mit.edu/lavacorpus/>PDF icon D15-1172.pdf (2.42 MB)
Mhaskar, H., Liao, Q. & Poggio, T. Learning Functions: When Is Deep Better Than Shallow. (2016). at <https://arxiv.org/pdf/1603.00988v4.pdf>
Mlynarski, W. & McDermott, J. H. Learning mid-level codes for natural sounds. Computational and Systems Neuroscience (Cosyne) 2016 (2016). at <http://www.cosyne.org/c/index.php?title=Cosyne2016_posters_2>PDF icon Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Codes for Natural Sounds. Advances and Perspectives in Auditory Neuroscience (2016).PDF icon APAN_large_JHM kopia.pdf (19.74 MB)

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