All Publications

2019

T. D. Ullman, Kosoy, E., Yildirim, I., Soltani, A. Arsalan, Siegel, M., Tenenbaum, J. B., and Spelke, E. S., “Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects”, Cognitive Science Society. Montreal, Canada, 2019.PDF icon Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects.pdf (2.62 MB)
CBMM Funded
A. Adler, Araya-Polo, M., and Poggio, T., “Deep Recurrent Architectures for Seismic Tomography”, in 81st EAGE Conference and Exhibition 2019, 2019.
CBMM Funded
A. Banburski, Liao, Q., Miranda, B., Rosasco, L., Hidary, J., and Poggio, T., “Weight and Batch Normalization implement Classical Generalization Bounds ”, in ICML, Long Beach/California, 2019.
CBMM Funded
A. Barbu, Banda, D., and Katz, B., “Deep video-to-video transformations for accessibility with an application to photosensitivity”, Pattern Recognition Letters, 2019.
CBMM Funded
S. V. Norman-Haignere, Kanwisher, N., McDermott, J. H., and Conway, B. R., “Divergence in the functional organization of human and macaque auditory cortex revealed by fMRI responses to harmonic tones”, Nature Neuroscience, 2019.
CBMM Funded
J. P. McCoy and Ullman, T., “Judgments of effort for magical violations of intuitive physics”, PLOS ONE, vol. 14, no. 5, p. e0217513, 2019.
CBMM Related
CBMM Memo No.
098
H. Mhaskar and Poggio, T., “An analysis of training and generalization errors in shallow and deep networks”. 2019.PDF icon CBMM-Memo-098.pdf (687.36 KB)PDF icon CBMM Memo 098 v4 (08/2019) (2.63 MB)
CBMM Funded
P. Bashivan, Kar, K., and DiCarlo, J. J., “Neural Population Control via Deep Image Synthesis”, Science, vol. 364, no. 6439, 2019.PDF icon Author's last draft (18.45 MB)
CBMM Funded
Y. Han, Roig, G., Geiger, G., and Poggio, T., “Properties of invariant object recognition in human one-shot learning suggests a hierarchical architecture different from deep convolutional neural networks”, in Vision Science Society, Florida, USA, 2019.
CBMM Funded
Y. Han, Roig, G., Geiger, G., and Poggio, T., “Properties of invariant object recognition in human oneshot learning suggests a hierarchical architecture different from deep convolutional neural networks ”, in Vision Science Society, St Pete Beach, FL, USA, 2019.
CBMM Funded
C. R. Ponce, Xiao, W., Schade, P. F., Hartmann, T. S., Kreiman, G., and Livingstone, M. S., “Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences”, Cell , vol. 177, p. 1009, 2019.PDF icon Author's last draft (20.26 MB)
CBMM Funded
J. Serrino, Kleiman-Weiner, M., Parkes, D. C., and Tenenbaum, J. B., “Finding Friend and Foe in Multi-Agent Games”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon Max KW paper.pdf (928.96 KB)
CBMM Funded
J. Zhang, Han, Y., Poggio, T., and Roig, G., “Eccentricity Dependent Neural Network with Recurrent Attention for Scale, Translation and Clutter Invariance ”, in Vision Science Society, Florida, USA, 2019.
CBMM Funded
K. Kar, Kubilius, J., Schmidt, K., Issa, E. B., and DiCarlo, J. J., “Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior”, Nature Neuroscience, 2019.PDF icon Author's last draft (1.74 MB)
CBMM Funded
O. Lewis and Hermann, K., “Data for free: Fewer-shot algorithm learning with parametricity data augmentation”, in ICLR 2019, 2019.
CBMM Related
Y. Vazquez, Ianni, G., and Freiwald, W. A., “Neural mechanisms supporting facial expressions ”, in unknown, New York, NY, USA, 2019.
CBMM Funded
A. Banburski, Liao, Q., Miranda, B., Rosasco, L., Hidary, J., and Poggio, T., “Dynamics & Generalization in Deep Networks -Minimizing the Norm”, in NAS Sackler Colloquium on Science of Deep Learning, Washington D.C., 2019.
CBMM Funded
M. A. P. Idiart, Villavicencio, A., Katz, B., Rennó-Costa, C., and Lisman, J., “How Does the Brain Represents Language and Answers Questions? Using an AI System to Understand the Underlying Neurobiological Mechanisms”, Frontiers in Computational Neuroscience, vol. 13, 2019.
CBMM Funded
E. H. Patzelt, Kool, W., Millner, A. J., and Gershman, S. J., “Incentives Boost Model-Based Control Across a Range of Severity on Several Psychiatric Constructs”, Biological Psychiatry, vol. 85, no. 5, pp. 425 - 433, 2019.
CBMM Funded
B. Deen and Saxe, R., “Parts‐based representations of perceived face movements in the superior temporal sulcus”, Human Brain Mapping, vol. 40, no. 8, pp. 2499 - 2510, 2019.
CBMM Funded
S. J. Gershman, “How to never be wrong”, Psychonomic Bulletin & Review, vol. 26, no. 1, pp. 13 - 28, 2019.
CBMM Funded
E. H. Patzelt, Kool, W., Millner, A. J., and Gershman, S. J., “The transdiagnostic structure of mental effort avoidance”, Scientific Reports, vol. 9, no. 1, 2019.
CBMM Related
S. Ullman, “Using neuroscience to develop artificial intelligence”, Science, vol. 363, no. 6428, pp. 692 - 693, 2019.
CBMM Related
S. Ullman, Dorfman, N., and Harari, D., “A model for discovering ‘containment’ relations”, Cognition, vol. 183, pp. 67 - 81, 2019.
CBMM Related
A. Adler and Wax, M., “Blind Constant Modulus Multiuser Detection via Low-Rank Approximation”, IEEE Signal Processing Letters, pp. 1 - 1, 2019.
CBMM Funded

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