Publication

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2019
Calero, C. I., Shalom, D. E., Spelke, E. S. & Sigman, M. Language, gesture, and judgment: Children’s paths to abstract geometry. Journal of Experimental Child Psychology 177, 70 - 85 (2019).
Srivastava, S., Ben-Yosef, G. & Boix, X. Minimal images in deep neural networks: Fragile Object Recognition in Natural Images. International Conference on Learning Representations (ICLR) (2019). at <https://arxiv.org/pdf/1902.03227.pdf>
Ullman, S., Dorfman, N. & Harari, D. A model for discovering ‘containment’ relations. Cognition 183, 67 - 81 (2019).
Bashivan, P., Kar, K. & DiCarlo, J. J. Neural Population Control via Deep Image Synthesis. Science 364, (2019).PDF icon Author's last draft (18.45 MB)
Liu, S., Brooks, N. B. & Spelke, E. S. Origins of the concepts cause, cost, and goal in prereaching infants. PNAS (2019). doi:https://doi.org/10.1073/pnas.1904410116PDF icon Author's last draft (2.58 MB)
Fazeli, N. et al. See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion. Science Robotics 4, eaav3123 (2019).
Isik, L., Mynick, A., Pantazis, D. & Kanwisher, N. The speed of human social interaction perception. BioRxiv (2019). doi:https://doi.org/10.1101/579375
Patzelt, E. H., Kool, W., Millner, A. J. & Gershman, S. J. The transdiagnostic structure of mental effort avoidance. Scientific Reports 9, (2019).
Ullman, S. Using neuroscience to develop artificial intelligence. Science 363, 692 - 693 (2019).
2018
Mhaskar, H. & Poggio, T. An analysis of training and generalization errors in shallow and deep networks. (2018).PDF icon CBMM-Memo-076.pdf (772.61 KB)
Berzak, Y., Katz, B. & Levy, R. Assessing Language Proficiency from Eye Movements in Reading. 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2018). at <http://naacl2018.org/>PDF icon 1804.07329.pdf (350.43 KB)
Spokes, A. C. & Spelke, E. S. At 4.5 but not 5.5 years, children favor kin when the stakes are moderately high. PLOS ONE 13, (2018).
Xiao, W., Chen, H., Liao, Q. & Poggio, T. Biologically-plausible learning algorithms can scale to large datasets. (2018).PDF icon CBMM-Memo-092.pdf (1.31 MB)
Muir, D., Fang, X. & Meyers, E. Brain-Observatory-Toolbox. (2018).
Liao, Q., Miranda, B., Hidary, J. & Poggio, T. Classical generalization bounds are surprisingly tight for Deep Networks. (2018).PDF icon CBMM-Memo-091.pdf (1.43 MB)PDF icon CBMM-Memo-091-v2.pdf (1.88 MB)
Sliwa, J., Marvel, S. R., Ianni, G. A. & Freiwald, W. A. Comparing human and monkey neural circuits for processing social scenes. Société Francophone de Primatologie (SFDP) Annual Meeting, Paris, France (2018).
Sliwa, J., Marvel, S. R., Ianni, G. A. & Freiwald, W. A. Comparing human and monkey neural circuits for processing social scenes. Cognitive Neuroscience Society Annual Meeting (CNS), Boston, MA (2018).
Sliwa, J., Marvel, S. R., Ianni, G. A. & Freiwald, W. A. Comparing human and monkey neural circuits for processing social scenes. Social & Affective Neuroscience Society (SANS) (2018). at <http://www.socialaffectiveneuro.org/conferences.html>
Zisselman, E., Adler, A. & Elad, M. Handbook of Numerical Analysis 19, 3 - 17 (Elsevier, 2018).
Dehghani, N. & Wimmer, R. A computational perspective of the role of Thalamus in cognition. arxiv (2018). at <https://arxiv.org/abs/1803.00997>PDF icon ThalamusComputationArxiv.pdf (5.12 MB)
Adler, A. & Wax, M. Constant Modulus Algorithms via Low-Rank Approximation. (2018).PDF icon CBMM-Memo-077.pdf (795.61 KB)
Adler, A. & Wax, M. Constant Modulus Beamforming Via Low-Rank Approximation. 2018 IEEE Statistical Signal Processing Workshop (SSP) (2018). doi:10.1109/SSP.2018.8450799
Mlynarski, W. & McDermott, J. H. Co-occurrence statistics of natural sound features predict perceptual grouping. Computational and Systems Neuroscience (COSYNE) (2018). at <http://www.cosyne.org/c/index.php?title=Cosyne_18>
Mlynarski, W. & McDermott, J. H. Co-occurrence statistics of natural sound features predict perceptual grouping. Computational and Systems Neuroscience (Cosyne) 2018 (2018).
Livingstone, M. S., Arcaro, M. J. & Schade, P. F. Cortex Is Cortex: Ubiquitous Principles Drive Face-Domain Development. Trends in Cognitive Sciences (2018). doi:10.1016/j.tics.2018.10.009PDF icon 1-s2.0-S1364661318302572-main.pdf (260.4 KB)

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