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2015
Koch, C. & Poggio, T. A Science of Intelligence . (2015).PDF icon A Science of Intelligence.pdf (659.5 KB)
Wang, J. & Yuille, A. Semantic Part Segmentation using Compositional Model combing Shape and Appearance. CVPR (2015).PDF icon JianyuWangSemanticCVPR2015 (1).pdf (6.15 MB)
Singer, J., Madsen, J., Anderson, W. S. & Kreiman, G. Sensitivity to timing and order in human visual cortex. Journal of Neurophysiology 113, 1656 - 1669 (2015).
Liu, S. & Spelke, E. S. Six-month-old infants represent action efficiency on a continuous scale. 9th Biennial Meeting of the Cognitive Development Society (CDS) (2015).
Shrobe, H., Katz, B. & Davis, R. Towards a Programmer's Apprentice (Again). (2015).PDF icon CBMM-memo-030.pdf (294.27 KB)
Cormiea, S., Vaziri-Pashkam, M. & Nakayama, K. Unconscious perception of an opponent's goal. Vision Sciences Society Annual Meeting (VSS 2015) (2015). doi:10.1167/15.12.43
Anselmi, F. et al. Unsupervised learning of invariant representations. Theoretical Computer Science (2015). doi:10.1016/j.tcs.2015.06.048
Lotter, W., Kreiman, G. & Cox, D. UNSUPERVISED LEARNING OF VISUAL STRUCTURE USING PREDICTIVE GENERATIVE NETWORKS. (2015).PDF icon CBMM Memo 040_rev1.pdf (1.92 MB)
Powell, L. J., Deen, B., Guo, L. & Saxe, R. Using fNIRS to Map Functional Specificity in the Infant Brain: An fROI Approach. (2015).PDF icon SRCD2015_NIRS_poster.pdf (2.14 MB)
de la Rosa, S. et al. Visual categorization of social interactions. Visual Cognition 22, (2015).
Poggio, T. What if.. (2015).PDF icon What if.pdf (2.09 MB)
Fisher, C. & Freiwald, W. A. Whole-agent selectivity within the macaque face-processing system. Proceedings of the National Academy of Sciences (PNAS) 112, (2015).PDF icon Authors' last version of article.  (3.1 MB)
Mendoza-Halliday, D., Torres, S. & Martinez-Trujillo, J. Mechanisms of Sensory Working Memory: Attention and Performance XXV. (Elsevier Inc. , 2015). at <https://www.sciencedirect.com/book/9780128013717/mechanisms-of-sensory-working-memory>
Dillon, M. R. & Spelke, E. S. Young children’s automatic and alternating use of scene and object information in spatial symbols. Budapest CEU Conference on Cognitive Development (2015).
2014
Amir, N. et al. Abstracts of the 2014 Brains, Minds, and Machines Summer Course. (2014).PDF icon CBMM-Memo-024.pdf (2.86 MB)
Liao, Q., Leibo, J. Z., Mroueh, Y. & Poggio, T. Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines?. (2014).PDF icon CBMM-Memo-003.pdf (963.66 KB)
Barbu, A. et al. The Compositional Nature of Event Representations in the Human Brain. (2014).PDF icon CBMM Memo 011.pdf (3.95 MB)
Poggio, T., Mutch, J. & Isik, L. Computational role of eccentricity dependent cortical magnification. (2014).PDF icon CBMM-Memo-017.pdf (1.04 MB)
Goodman, N. D., Tenenbaum, J. B. & Gerstenberg, T. Concepts in a Probabilistic Language of Thought. (2014).PDF icon CBMM-Memo-010.pdf (902.53 KB)
Dillon, M. R. & Spelke, E. S. Core geometry in perspective. Developmental Science (2014). doi:10.1111/desc.12266
Nassi, J. J., Gomez-Laberge, C., Kreiman, G. & Born, R. T. Corticocortical feedback increases the spatial extent of normalization. Frontiers in Systems Neuroscience 8, 105 (2014).
Rutishauser, U., Cerf, M. & Kreiman, G. Single Neuron Studies of the Brain: Probing Cognition (2014).
Zhang, C., Evangelopoulos, G., Voinea, S., Rosasco, L. & Poggio, T. A Deep Representation for Invariance and Music Classification. ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE, 2014). doi:10.1109/ICASSP.2014.6854954
Zhang, C., Evangelopoulos, G., Voinea, S., Rosasco, L. & Poggio, T. A Deep Representation for Invariance And Music Classification. (2014).PDF icon CBMM-Memo-002.pdf (1.63 MB)
Chen, X. et al. Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts. (2014).PDF icon CBMM-Memo-015.pdf (974.07 KB)

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