Publication

Found 230 results
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2015
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)
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)
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)
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)
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. J Neurophysiol 111, 91-102 (2014).
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
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)
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)
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)
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)
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)
Linderman, S. W., Johnson, M. J., Wilson, M. A. & Chen, Z. A Nonparametric Bayesian Approach to Uncovering Rat Hippocampal Population Codes During Spatial Navigation. (2014).PDF icon CBMM-Memo-027.pdf (9.44 MB)
Lu, W., Lian, X. & Yuille, A. Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency. (2014).PDF icon CBMM-Memo-018_opt.pdf (5.02 MB)
Lu, W., Lian, X. & Yuille, A. Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency. (2014).PDF icon CBMM-Memo-018_opt.pdf (5.02 MB)
Wang, C., Wang, Y., Lin, Z., Yuille, A. & Gao, W. Robust Estimation of 3D Human Poses from a Single Image. (2014).PDF icon CBMM-Memo-013.pdf (510.23 KB)
Li, Y., Koch, C., Rehg, J. M. & Yuille, A. The Secrets of Salient Object Segmentation. (2014).PDF icon CBMM-Memo-014.pdf (1.59 MB)
Leibo, J. Z., Liao, Q. & Poggio, T. Subtasks of unconstrained face recognition. (2014).
Leibo, J. Z., Liao, Q. & Poggio, T. Subtasks of unconstrained face recognition. (2014).
Leibo, J. Z., Liao, Q. & Poggio, T. Subtasks of Unconstrained Face Recognition. (2014).PDF icon Leibo_Liao_Poggio_subtasks_VISAPP_2014.pdf (268.69 KB)
Leibo, J. Z., Liao, Q. & Poggio, T. Subtasks of Unconstrained Face Recognition. (2014).PDF icon Leibo_Liao_Poggio_subtasks_VISAPP_2014.pdf (268.69 KB)
Liao, Q., Leibo, J. Z. & Poggio, T. Unsupervised learning of clutter-resistant visual representations from natural videos. (2014).PDF icon 1409.3879v2.pdf (3.64 MB)
Liao, Q., Leibo, J. Z. & Poggio, T. Unsupervised learning of clutter-resistant visual representations from natural videos. (2014).PDF icon 1409.3879v2.pdf (3.64 MB)

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