All Publications

2016

T. Gerstenberg and Tenenbaum, J. B., “Understanding "almost": Empirical and computational studies of near misses”, 38th Annual Meeting of the Cognitive Science Society. 38th Annual Meeting of the Cognitive Science Society, 2016.PDF icon Understanding almost (Gerstenberg, Tenenbaum, 2016).pdf (4.08 MB)
CBMM Funded
C. Gómez-Laberge, Smolyanskaya, A., Nassi, J. J., Kreiman, G., and Born, R. T., “Bottom-up and Top-down Input Augment the Variability of Cortical Neurons.”, Neuron, vol. 91(3), pp. 540-547, 2016.
CBMM Funded
J. K. Hartshorne, “VerbCorner: Testing theories of argument structure through crowdsourcing”, Workshop on Events in Language. 2016.PDF icon VerbCorner_EventsInLanguage.pdf (1.14 MB)
CBMM Related
J. Jara-Ettinger, Gweon, H., Schulz, L., and Tenenbaum, J. B., “The naive utility calculus: computational principles underlying social cognition”, Trends Cogn Sci., 2016.
CBMM Funded
J. Jara-Ettinger, Piantadosi, S., Spelke, E. S., Levy, R., and Gibson, E., “Mastery of the logic of natural numbers is not the result of mastery of counting: Evidence from late counters. ”, Developmental Science, 2016.
CBMM Related
M. Kleiman-Weiner, Ho, M. K., Austerweil, J. L., L, L. Michael, and Tenenbaum, J. B., “Coordinate to cooperate or compete: abstract goals and joint intentions in social interaction”, in Proceedings of the 38th Annual Conference of the Cognitive Science Society, 2016.PDF icon kleiman2016coordinate.pdf (266.87 KB)
CBMM Related
D. Kliemann, Jacoby, N., Anzellottti, S., and Saxe, R., “Decoding task and stimulus representations in face-responsive cortex”, Cognitive Neuropsychology, 2016.
CBMM Related
M. Le Van Quyen, Muller, L., Telenczuk, B., Halgren, E., Cash, S., Hatsopoulos, N., Dehghani, N., and Destexhe, A., “High-frequency oscillations in human and monkey neocortex during the wake–sleep cycle”, Proceedings of the National Academy of Sciences, 2016.PDF icon BetaGammaSleepAwakeFull.pdf (3.68 MB)
CBMM Related
Q. Liao, Leibo, J. Z., and Poggio, T., “How Important Is Weight Symmetry in Backpropagation?”, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, AZ., 2016.
CBMM Funded
I. Lifshitz, Fetaya, E., and Ullman, S., “Human Pose Estimation Using Deep Consensus Voting”, in ECCV 2016, 2016.PDF icon 1603.08212.pdf (6.05 MB)
CBMM Funded
S. W. Linderman, Johnson, M. J., Wilson, M. A., and Chen, Z., “A Bayesian nonparametric approach for uncovering rat hippocampal population codes during spatial navigation”, Journal of Neuroscience Methods, vol. 263, no. 1, 2016.PDF icon Journal of Neuroscience Methods (2.27 MB)
CBMM Related
W. Lotter, Kreiman, G., and Cox, D., “PredNet - "Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning" [code]”. 2016.
CBMM Related
J. Mao, Xu, J., Jing, Y., and Yuille, A., “Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images”, in NIPS 2016, 2016.PDF icon 6590-training-and-evaluating-multimodal-word-embeddings-with-large-scale-web-annotated-images.pdf (1.57 MB)
CBMM Funded
E. Meyers, Dean, M., and Hale, G. J., “New Data Science tools for analyzing neural data and computational models”, Society for Neuroscience. 2016.
CBMM Funded
T. Miconi, Groomes, L., and Kreiman, G., “There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task”, Cerebral Cortex, vol. 26(7), pp. 26:3064-3082, 2016.
CBMM Funded
T. Miconi, Groomes, L., and Kreiman, G., “There’s Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task [code]”. 2016.
CBMM Funded
T. Miconi, Groomes, L., and Kreiman, G., “There’s Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task [dataset]”. 2016.
CBMM Funded
W. Mlynarski and McDermott, J. H., “Learning Mid-Level Codes for Natural Sounds”, Advances and Perspectives in Auditory Neuroscience. 2016.PDF icon APAN_large_JHM kopia.pdf (19.74 MB)
CBMM Funded
W. Mlynarski and McDermott, J. H., “Lossy Compression of Sound Texture by the Human Auditory System”, Society for Neuroscience Meeting. 2016.
CBMM Funded
A. Morales, Premtoon, V., Avery, C., Felshin, S., and Katz, B., “Learning to Answer Questions from Wikipedia Infoboxes”, in The 2016 Conference on Empirical Methods on Natural Language Processing (EMNLP 2016), 2016.PDF icon Morales-EMNLP2016.pdf (197.28 KB)
CBMM Funded
M. Nickel, Rosasco, L., and Poggio, T., “Holographic Embeddings of Knowledge Graphs”, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, USA, 2016.PDF icon 1510.04935v2.pdf (360.65 KB)
CBMM Funded
F. Peres, Smith, K. A., and Tenenbaum, J. B., “Rapid Physical Predictions from Convolutional Neural Networks”, Neural Information Processing Systems, Intuitive Physics Workshop. 2016.PDF icon Rapid Physical Predictions - NIPS Physics Workshop Poster (1.47 MB)
CBMM Related
M. F. Peterson, Lin, J., Zaun, I., and Kanwisher, N., “Individual differences in face-looking behavior generalize from the lab to the world.”, Journal of Vision, 2016.
CBMM Funded
J. Sliwa and Freiwald, W. A., “From agents to actions to interactions: Uncovering multiple social networks in the primate brain”, Society for Neuroscience. 2016.PDF icon SFN2016.pdf (555.77 KB)
CBMM Related
E. S. Spelke, Barner, D., and Baron, A. S., “Core knowledge and conceptual change: A perspective on social cognition”, in Core Knowledge and Conceptual Change, New York: Oxford University Press, 2016.
CBMM Related

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