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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)
Isik, L., Meyers, E., Leibo, J. Z. & Poggio, T. The dynamics of invariant object recognition in the human visual system. (2014). doi:http://dx.doi.org/10.7910/DVN/KRUPXZ
Isik, L., Meyers, E., Leibo, J. Z. & Poggio, T. The dynamics of invariant object recognition in the human visual system. J Neurophysiol 111, 91-102 (2014).
Stern, M., Sompolinsky, H. & Abbott, L. F. Dynamics of random neural networks with bistable units. Phys Rev E Stat Nonlin Soft Matter Phys 90, (2014).
Yildirim, I., Kulkarni, T., Freiwald, W. A. & Tenenbaum, J. B. Explaining Monkey Face Patch System as Efficient Analysis-by-Synthesis. (2014).PDF icon yildirimetal_cosyne15.pdf (313.57 KB)
Deen, B., Kanwisher, N. & Saxe, R. Exploring the functional organization of the superior temporal sulcus with a broad set of naturalistic stimuli. (2014).
Linderman, S. W., Stock, C. & Adams, R. A framework for studying synaptic plasticity with neural spike train data. Neural Information Processing Systems (2014).PDF icon 5274-a-framework-for-studying-synaptic-plasticity-with-neural-spike-train-data.pdf (4.6 MB)
Winston, P. Henry. The Genesis Story Understanding and Story Telling System A 21st Century Step toward Artificial Intelligence. (2014).PDF icon CBMM-Memo-019_StoryWhitePaper.pdf (894.38 KB)
Mottaghi, R., Fidler, S., Yuille, A., Urtasun, R. & Parikh, D. Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding. (2014).PDF icon CBMM-Memo-020.pdf (1.89 MB)
Kosakowski, H. L., Powell, L. J. & Spelke, E. S. Imitation Preferences of Preverbal Infants. CBMM Summer Research Program (2014).PDF icon Imitation Preferences of Preverbal Infants. (11.32 MB)
Leibo, J. Z., Liao, Q., Anselmi, F. & Poggio, T. The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. (2014). doi:10.1101/004473PDF icon CBMM Memo 004_new.pdf (2.25 MB)
Evangelopoulos, G., Voinea, S., Zhang, C., Rosasco, L. & Poggio, T. Learning An Invariant Speech Representation. (2014).PDF icon CBMM-Memo-022-1406.3884v1.pdf (1.81 MB)
Liao, Q., Leibo, J. Z. & Poggio, T. Learning invariant representations and applications to face verification. NIPS 2013 (Advances in Neural Information Processing Systems 26, 2014). at <http://nips.cc/Conferences/2013/Program/event.php?ID=4074>PDF icon Liao_Leibo_Poggio_NIPS_2013.pdf (687.06 KB)

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