Publication

Export 550 results:
2017
Magid, R., Yan, P., Siegel, M., Tenenbaum, J. B. & Schulz, L. Changing minds: Children’s inferences about third party belief revision. Developmental Science e12553 (2017). doi:10.1111/desc.12553PDF icon Changing Minds_MagidYanSiegelTenenbaumSchulz_in press.pdf (915.8 KB)
Winston, P. Henry & Holmes, D. Character-building stories. Advances in Cognitive Systems (2017).
Jara-Ettinger, J., Floyd, S., Tenenbaum, J. B. & Schulz, L. Children understand that agents maximize expected utilities. Journal of Experimental Psychology: General 146, 1574 - 1585 (2017).PDF icon ExpectedUtilities_Final.pdf (950.09 KB)
Sliwa, J., Marvel, S. R. & Freiwald, W. A. Comparing human and monkey neural circuits for processing social scenes. Society for Neuroscience's Annual Meeting - SfN 2017 (2017).
Schulz, E., Tenenbaum, J. B., Duvenaud, D., Speekenbrink, M. & Gershman, S. J. Compositional inductive biases in function learning. Cogn Psychol 99, 44-79 (2017).
Chandrasekhar, V. et al. Compression of Deep Neural Networks for Image Instance Retrieval. (2017). at <https://arxiv.org/abs/1701.04923>PDF icon 1701.04923.pdf (614.33 KB)
Kool, W., Gershman, S. J. & Cushman, F. A. Cost-Benefit Arbitration Between Multiple Reinforcement-Learning Systems. Psychol Sci 28, 1321-1333 (2017).
Spokes, A. C. & Spelke, E. S. The cradle of social knowledge: Infants' reasoning about caregiving and affiliation. Cognition 159, 102-116 (2017).
Ullman, T., Tenenbaum, J. B. & Spelke, E. S. Critical Cues in Early Physical Reasoning. SRCD (2017).
Meyers, E. A Data Science approach to analyzing neural data. Joint Statistical Meetings (2017).
Chen, Z. & Wilson, M. A. Deciphering neural codes of memory during sleep. Trends in Neurosciences (2017).PDF icon proof (2.98 MB)
Sliwa, J. & Freiwald, W. A. A Dedicated Network for Social Interaction Processing in the Primate Brain. Science Vol. 356, pp. 745-749 (2017).
Lotter, W., Kreiman, G. & Cox, D. Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. (2017).PDF icon CBMM-Memo-064.pdf (3 MB)
Lotter, W., Kreiman, G. & Cox, D. Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. ICLR (2017).PDF icon 1605.08104.pdf (2.9 MB)
Dehghani, N. Design of the Artificial: lessons from the biological roots of general intelligence. (2017). at <https://arxiv.org/pdf/1703.02245>PDF icon DesignArtificial_Dehghani_arXiv.pdf (222.47 KB)
Wang, J. et al. Detecting Semantic Parts on Partially Occluded Objects. (2017).PDF icon CBMM-Memo-078.pdf (1.74 MB)
Wang, J. et al. Detecting Semantic Parts on Partially Occluded Objects. British Machine Vision Conference (BMVC) (2017). at <https://bmvc2017.london/proceedings/>
Meyers, E., Riley, M., Qi, X. - L. & Constantinidis, C. Differences in dynamic and static coding within different subdivision of the prefrontal cortex. Society for Neuroscience's Annual Meeting - SfN 2017 (2017). at <http://www.abstractsonline.com/pp8/#!/4376/presentation/4782>
Meyers, E., Liang, A., Katsuki, F. & Constantinidis, C. Differential Processing of Isolated Object and Multi-item Pop-Out Displays in LIP and PFC. Cerebral Cortex (2017). doi:10.1093/cercor/bhx243
Tacchetti, A., Voinea, S. & Evangelopoulos, G. Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets. (2017).PDF icon CBMM-Memo-062.pdf (9.37 MB)
Volokitin, A., Roig, G. & Poggio, T. Do Deep Neural Networks Suffer from Crowding?. (2017).PDF icon CBMM-Memo-069.pdf (6.47 MB)
Volokitin, A. & Roig, G. Do Deep Neural Networks Suffer from Crowding? [code]. (2017).
Roig, G., Chen, F., Boix, X. & Poggio, T. Eccentricity Dependent Deep Neural Networks for Modeling Human Vision. Vision Sciences Society (2017).
Chen, F., Roig, G., Isik, L., Boix, X. & Poggio, T. Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision. AAAI Spring Symposium Series, Science of Intelligence (2017). at <https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15360>PDF icon paper.pdf (963.87 KB)
N. Murty, A. Ratan & Arun, S. P. Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex. Journal of Neurophysiology 11823, 353 - 362 (2017).

Pages