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Leibo, J. Z., Liao, Q., Freiwald, W. A., Anselmi, F. & Poggio, T. View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation. (2016).PDF icon faceMirrorSymmetry_memo_ver01.pdf (3.93 MB)
Rosenfeld, A. & Ullman, S. Visual Concept Recognition and Localization via Iterative Introspection. . Asian Conference on Computer Vision (2016).PDF icon Focusing on parts of interest  (910.14 KB)
Poggio, T. & Anselmi, F. Visual Cortex and Deep Networks: Learning Invariant Representations. 136 (The MIT Press, 2016). at <>
Owens, A. et al. Visually indicated sounds. Conference on Computer Vision and Pattern Recognition (2016).PDF icon Owens_etal_2016_visually_indicated_sounds_CVPR.pdf (7.57 MB)
Spokes, A. C., Howard, R., Mehr, S. A. & Krasnow, M. M. Welfare-tradeoff ratios in children. Human Behavior and Evolution Society (2016).
Kool, W., Cushman, F. A. & Gershman, S. J. When Does Model-Based Control Pay Off?. PLoS Comput Biol 12, e1005090 (2016).PDF icon KoolEtAl_PLOS_CB.PDF (5.85 MB)
Dasgupta, I., Schulz, E. & Gershman, S. J. Where do hypotheses come from?. (2016).PDF icon CBMM-Memo-056-v2.pdf (733.35 KB)
Dillon, M. R. & Spelke, E. S. Young Children’s Use of Surface and Object Information in Drawings of Everyday Scenes. Child Development (2016). doi:10.1111/cdev.12658
Xia, F., Wang, P., Chen, L. -chieh & Yuille, A. Zoom better to see clearer: Human and object parsing with hierarchical auto-zoom net. ECCV (2016).PDF icon auto-zoom_net.pdf (5.77 MB)
Xia, F., Wang, P., Chen, L. -chieh & Yuille, A. Zoom Better to See Clearer: Human Part Segmentation with Auto Zoom Net. ECCV (2016).
Atabaki, A., Marciniak, K., Dicke, P. W. & Thier, P. Assessing the precision of gaze following using a stereoscopic 3D virtual reality setting. Vision Res 112, 68-82 (2015).PDF icon Atabaki Marciniak Dicke Thier 2015 Vis Res Assesing the precision of gaze following using a stereoscopic 3D virtual reality setting.pdf (2.52 MB)
Hawrylycz, M. et al. Canonical genetic signatures of the adult human brain. Nature Neuroscience 18, 1844 (2015).PDF icon Preprint (40.28 MB)
Hartshorne, J. K. The causes and consequences explicit in verbs. Language, Cognition and Neuroscience 30, 716-734 (2015).
Jara-Ettinger, J., Gweon, H., Tenenbaum, J. B. & Schulz, L. Children’s understanding of the costs and rewards underlying rational action. Cognition 140, 14–23 (2015).PDF icon CM_inPress.pdf (438.5 KB)
Dillon, M. R., Pires, A. C., Hyde, D. C. & Spelke, E. S. Children's expectations about training the approximate number system. British Journal of Developmental Psychology 33, (2015).
Yuille, A. & Mottaghi, R. Complexity of Representation and Inference in Compositional Models with Part Sharing. (2015).PDF icon CBMM Memo 031.pdf (1.14 MB)
Yu, H., Siddharth, N., Barbu, A. & Siskind, J. Mark. A Compositional Framework for Grounding Language Inference, Generation, and Acquisition in Video. (2015). doi:doi:10.1613/jair.4556
Gershman, S. J., Horvitz, E. J. & Tenenbaum, J. B. Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. Science 349, 273-278 (2015).
Dillon, M. R. & Spelke, E. S. Connecting core cognition, spatial symbols, and the abstract concepts of formal geometry. Cognitive Development Society Post-Conference, More on Development (2015).
Koch, C. & Tononi, G. Consciousness: here, there and everywhere?. Phil. Trans. Roy Society B 370, (2015).PDF icon Tononi & Koch '15.pdf (1.87 MB)
Fisher, C. & Freiwald, W. A. Contrasting Specializations for Facial Motion within the Macaque Face-Processing System. Current Biology 25, (2015).PDF icon Facial Motion Selectivity in the Macaque Brain (1.43 MB)
Berzak, Y., Reichart, R. & Katz, B. Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL. Nineteenth Conference on Computational Natural Language Learning (CoNLL), Beijing, China (2015).
Kliemann, D., Jacoby, N., Anzellottti, S. & Saxe, R. Decoding task and stimulus representation in face-responsive cortex. (2015).
Madhavan, R. et al. Decrease in gamma-band activity tracks sequence learning. Frontiers in Systems Neuroscience 8, (2015).PDF icon fnsys-08-00222.pdf (5.62 MB)
Mao, J. et al. Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN). (2015).PDF icon CBMM Memo 033.pdf (839.42 KB)