Publication

Found 247 results
Author Title Type [ Year(Desc)]
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2012
Mutch, J. & Turaga, S. cnpkg: 3-D Convolutional Network Package for CNS. (2012).File cnpkg.tar (50 KB)
2013
Anselmi, F. et al. Unsupervised Learning of Invariant Representations in Hierarchical Architectures. (2013).PDF icon 1311.4158v2.pdf (3.78 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)
Barbu, A. et al. The Compositional Nature of Event Representations in the Human Brain. (2014).PDF icon CBMM Memo 011.pdf (3.95 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)
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)
Tan, C. & Poggio, T. Neural tuning size is a key factor underlying holistic face processing. (2014).PDF icon CBMM-Memo-021-1406.3793.pdf (387.79 KB)
Krompaß, D., Nickel, M. & Tresp, V. The Semantic Web – ISWC 2014 8797, 114-129 (Springer International Publishing, 2014).
Nickel, M., Jiang, X. & Tresp, V. Advances in Neural Information Processing Systems 27 1179–1187 (Curran Associates, Inc., 2014). at <http://papers.nips.cc/paper/5448-reducing-the-rank-in-relational-factorization-models-by-including-observable-patterns.pdf>
Tang, H., Buia, C., Madsen, J., Anderson, W. S. & Kreiman, G. A role for recurrent processing in object completion: neurophysiological, psychophysical and computational evidence. (2014).PDF icon CBMM-Memo-009.pdf (4.21 MB)
Barbu, A. et al. Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions. (2014).PDF icon CBMM Memo 012.pdf (678.95 KB)
Barbu, A. et al. Computer Vision – ECCV 2014, Lecture Notes in Computer Science 8693, 612–627 (Springer International Publishing, 2014).
Mendoza-Halliday, D., Torres, S. & Martinez-Trujillo, J. Sharp emergence of feature-selective sustained activity along the dorsal visual pathway. Nature Neuroscience 7, (2014).
Tang, H. et al. Spatiotemporal Dynamics Underlying Object Completion in Human Ventral Visual Cortex. Neuron 83, 736 - 748 (2014).
Anselmi, F. et al. Unsupervised learning of invariant representations with low sample complexity: the magic of sensory cortex or a new framework for machine learning?. (2014).PDF icon CBMM Memo No. 001 (940.36 KB)
Gao, T., Harari, D., Tenenbaum, J. B. & Ullman, S. When Computer Vision Gazes at Cognition. (2014).PDF icon CBMM-Memo-025.pdf (3.78 MB)
2015
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)
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)
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).
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)
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)
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)
Anselmi, F., Rosasco, L., Tan, C. & Poggio, T. Deep Convolutional Networks are Hierarchical Kernel Machines. (2015).PDF icon CBMM Memo 035_rev5.pdf (975.65 KB)
Gershman, S. J., Tenenbaum, J. B. & Jaekel, F. Discovering hierarchical motion structure. Vision Research Available online 26 March 2015, (2015).PDF icon hierarchical_motion.pdf (582.01 KB)

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