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2016
Berzak, Y., Huang, Y., Barbu, A., Korhonen, A. & Katz, B. Anchoring and Agreement in Syntactic Annotations. (2016).PDF icon CBMM-Memo-055.pdf (768.54 KB)
Ullman, S., Assif, L., Fetaya, E. & Harari, D. Atoms of recognition in human and computer vision. PNAS 113, 2744–2749 (2016).PDF icon mirc_author_manuscript_with_figures_and_SI-2.pdf (1.65 MB)
Linderman, S. W., Johnson, M. J., Wilson, M. A. & Chen, Z. A Bayesian nonparametric approach for uncovering rat hippocampal population codes during spatial navigation. Journal of Neuroscience Methods 263, (2016).PDF icon Journal of Neuroscience Methods (2.27 MB)
Chen, Z., Linderman, S. W. & Wilson, M. A. Bayesian nonparametric methods for discovering latent structures of rat hippocampal ensemble spikes. IEEE Workshop on Machine Learning for Signal Processing (2016).PDF icon MLSP16 (1).pdf (1.04 MB)
Gómez-Laberge, C., Smolyanskaya, A., Nassi, J. J., Kreiman, G. & Born, R. T. Bottom-up and Top-down Input Augment the Variability of Cortical Neurons. Neuron 91(3), 540-547 (2016).
Liao, Q. & Poggio, T. Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex. (2016).PDF icon CBMM Memo No. 047 (1.29 MB)
Lake, B. M., Ullman, T., Tenenbaum, J. B. & Gershman, S. J. Building machines that learn and think like people. (2016).PDF icon machines_that_think.pdf (3.45 MB)
Tang, H. et al. Cascade of neural processing orchestrates cognitive control in human frontal cortex [code]. (2016). at <http://klab.tch.harvard.edu/resources/tangetal_stroop_2016.html>
Tang, H. et al. Cascade of neural processing orchestrates cognitive control in human frontal cortex [dataset]. (2016). at <http://klab.tch.harvard.edu/resources/tangetal_stroop_2016.html>
Tang, H. et al. Cascade of neural processing orchestrates cognitive control in human frontal cortex. eLIFE (2016). doi:10.7554/eLife.12352PDF icon Manuscript  (1.83 MB)
Spokes, A. C. & Spelke, E. S. Children’s Expectations and Understanding of Kinship as a Social Category. Frontiers in Psychology 7, 1664-1078 (2016).
Spelke, E. S., Sternberg, R. J., Fiske, S. T. & Foss, D. J. Scientists Making a Difference: One Hundred Eminent Behavioral and Brain Scientists Talk about Their Most Important Contributions (Cambridge University Press, 2016).
Lafer-Sousa, R., Conway, B. R. & 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 36, 1682 - 1697 (2016).
Liu, S. & Spelke, E. S. Continuous representations of action efficiency in infancy. CEU Conference on Cognitive Development (BCCCD16) (2016).
Berzak, Y., Reichart, R. & Katz, B. Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL. (2016).PDF icon memo-50.pdf (493.74 KB)
Kleiman-Weiner, M., Ho, M. K., Austerweil, J. L., L, L. Michael & Tenenbaum, J. B. Coordinate to cooperate or compete: abstract goals and joint intentions in social interaction. Proceedings of the 38th Annual Conference of the Cognitive Science Society (2016).PDF icon kleiman2016coordinate.pdf (266.87 KB)
Spelke, E. S., Barner, D. & Baron, A. S. Core Knowledge and Conceptual Change (Oxford University Press, 2016).
Lin, H. & Tegmark, M. Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language. arXiv.org (2016).PDF icon Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language (1.64 MB)
Kliemann, D., Jacoby, N., Anzellottti, S. & Saxe, R. Decoding task and stimulus representations in face-responsive cortex. Cognitive Neuropsychology (2016).
Poggio, T. Deep Leaning: Mathematics and Neuroscience. A Sponsored Supplement to Science Brain-Inspired intelligent robotics: The intersection of robotics and neuroscience, 9-12 (2016).
Poggio, T. Deep Learning: mathematics and neuroscience. (2016).PDF icon Deep Learning- mathematics and neuroscience.pdf (1.25 MB)
Mhaskar, H. & Poggio, T. Deep vs. shallow networks: An approximation theory perspective. Analysis and Applications 14, 829 - 848 (2016).
Mhaskar, H. & Poggio, T. Deep vs. shallow networks : An approximation theory perspective. (2016).PDF icon Original submission, visit the link above for the updated version (960.27 KB)
Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Do You See What I Mean? Visual Resolution of Linguistic Ambiguities. (2016).PDF icon memo-51.pdf (2.74 MB)

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