All Publications

2018

CBMM Memo No.
093
L. Arend, Han, Y., Schrimpf, M., Bashivan, P., Kar, K., Poggio, T., DiCarlo, J. J., and Boix, X., “Single units in a deep neural network functionally correspond with neurons in the brain: preliminary results”. 2018.PDF icon CBMM-Memo-093.pdf (2.99 MB)
CBMM Funded
CBMM Memo No.
092
W. Xiao, Chen, H., Liao, Q., and Poggio, T., “Biologically-plausible learning algorithms can scale to large datasets”. 2018.PDF icon CBMM-Memo-092.pdf (1.31 MB)
CBMM Funded
M. S. Livingstone, Arcaro, M. J., and Schade, P. F., “Cortex Is Cortex: Ubiquitous Principles Drive Face-Domain Development”, Trends in Cognitive Sciences, 2018.PDF icon 1-s2.0-S1364661318302572-main.pdf (260.4 KB)
CBMM Related
J. P. McCoy and Ullman, T. D., “A Minimal Turing Test”, Journal of Experimental Social Psychology, vol. 79, pp. 1 - 8, 2018.
CBMM Related
N. O'Brien, Latessa, S., Evangelopoulos, G., and Boix, X., “The Language of Fake News: Opening the Black-Box of Deep Learning Based Detectors”, in workshop on "AI for Social Good", NIPS 2018, Montreal, Canada, 2018.PDF icon fake-news-paper-NIPS.pdf (147.36 KB)PDF icon fake-news-paper-NIPS_2018_v2.pdf (147.36 KB)
CBMM Funded
J. Sliwa, Marvel, S. R., Ianni, G. A., and Freiwald, W. A., “Comparing human and monkey neural circuits for processing social scenes”, Société Francophone de Primatologie (SFDP) Annual Meeting, Paris, France. 2018.
CBMM Funded
L. Isik, Singer, J., Kanwisher, N., ,, WS, A., and Kreiman, G., “What is changing when: decoding visual information in movies from human intracranial recordings”, NeuroImage, vol. 180, Part A, pp. 147-159, 2018.PDF icon Human neurophysiological responses during movies (2.78 MB)
CBMM Funded
W. Kool, Gershman, S. J., and Cushman, F. A., “Planning Complexity Registers as a Cost in Metacontrol”, Journal of Cognitive Neuroscience, vol. 30, no. 10, pp. 1391 - 1404, 2018.
CBMM Funded
Y. - L. Kuo, Barbu, A., and Katz, B., “Deep sequential models for sampling-based planning”, in The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), Madrid, Spain, 2018.PDF icon kuo2018planning.pdf (637.67 KB)
CBMM Funded
E. Meyers, “Dynamic population coding and its relationship to working memory”, Journal of Neurophysiology, vol. 120, no. 5, pp. 2260 - 2268, 2018.
CBMM Funded
C. Ross, Barbu, A., Berzak, Y., Myanganbayar, B., and Katz, B., “Grounding language acquisition by training semantic parsersusing captioned videos”, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), , Brussels, Belgium, 2018.PDF icon Ross-et-al_ACL2018_Grounding language acquisition by training semantic parsing using caption videos.pdf (3.5 MB)
CBMM Funded
A. Tacchetti, Isik, L., and Poggio, T., “Invariant Recognition Shapes Neural Representations of Visual Input”, Annual Review of Vision Science, vol. 4, no. 1, pp. 403 - 422, 2018.PDF icon annurev-vision-091517-034103.pdf (1.55 MB)
CBMM Funded
E. Zisselman, Adler, A., and Elad, M., “Compressed Learning for Image Classification: A Deep Neural Network Approach”, in Handbook of Numerical Analysis, vol. 19, Elsevier, 2018, pp. 3 - 17.
CBMM Related
T. Owaki, Vidal-Naquet, M., Nam, Y., Uchida, G., Sato, T., Câteau, H., Ullman, S., and Tanifuji, M., “Searching for visual features that explain response variance of face neurons in inferior temporal cortex”, PLOS ONE, vol. 13, no. 9, p. e0201192, 2018.
CBMM Related
M. Zhang, Feng, J., Ma, K. Teck, Lim, J. Hwee, Zhao, Q., and Kreiman, G., “Finding any Waldo with zero-shot invariant and efficient visual search”, Nature Communications, vol. 9, 2018.
CBMM Funded
T. Gerstenberg, Ullman, T. D., Nagel, J., Kleiman-Weiner, M., Lagnado, D. A., and Tenenbaum, J. B., “Lucky or clever? From changed expectations to attributions of responsibility”, Cognition, 2018.
CBMM Funded
Y. Hart, Dillon, M. R., Marantan, A., Cardenas, A. L., Spelke, E. S., and Mahadevan, L., “The statistical shape of geometric reasoning”, Scientific Reports, vol. 8, no. 1, 2018.
CBMM Funded
J. Sliwa, Marvel, S. R., Ianni, G. A., and Freiwald, W. A., “Comparing human and monkey neural circuits for processing social scenes”, Organization for Computational Neurosciences - CNS 2018. Seattle, WA, 2018.
CBMM Related
A. C. Spokes and Spelke, E. S., “At 4.5 but not 5.5 years, children favor kin when the stakes are moderately high”, PLOS ONE, vol. 13, no. 8, 2018.
CBMM Related
H. Tang, Schrimpf, M., Lotter, W., Moerman, C., Paredes, A., Caro, J. Ortega, Hardesty, W., Cox, D., and Kreiman, G., “Recurrent computations for visual pattern completion”, Proceedings of the National Academy of Sciences, 2018.PDF icon 1719397115.full_.pdf (1.1 MB)
CBMM Funded
CBMM Memo No.
096
M. Zhang, Feng, J., Lim, J. Hwee, Zhao, Q., and Kreiman, G., “What am I searching for?”. 2018.PDF icon CBMM-Memo-096.pdf (1.74 MB)
CBMM Funded
CBMM Memo No.
091
Q. Liao, Miranda, B., Hidary, J., and 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)
CBMM Funded
W. Mlynarski and Hermundstad, A. M., “Adaptive Coding for Dynamic Sensory Inference”, eLife, 2018.
CBMM Funded
A. Palepu and Kreiman, G., “Development of automated interictal spike detector”, 40th International Conference of the IEEE Engineering in Medicine and Biology Society - EMBC 2018. Honolulu, HI, 2018.
CBMM Funded
R. Saxe, “Imaging the infant brain”, Japanese Society for Neuroscience, vol. Kobe Japan. 2018.
CBMM Related

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