All Publications

2021

D. McNamee, Stachenfeld, K., Botvinick, M. M., and Gershman, S. J., “Flexible modulation of sequence generation in the entorhinal-hippocampal system”, Nature Neuroscience, 2021.
CBMM Funded
C. Yang, Zhou, Y., Marcus, S., Formenti, G., Bergeron, L. A., Song, Z., Bi, X., Bergman, J., Rousselle, M. Marie C., Zhou, C., Zhou, L., Deng, Y., Fang, M., Xie, D., Zhu, Y., Tan, S., Mountcastle, J., Haase, B., Balacco, J., Wood, J., Chow, W., Rhie, A., Pippel, M., Fabiszak, M. M., Koren, S., Fedrigo, O., Freiwald, W. A., Howe, K., Yang, H., Phillippy, A. M., Schierup, M. Heide, Jarvis, E. D., and Zhang, G., “Evolutionary and biomedical insights from a marmoset diploid genome assembly”, Nature, 2021.
CBMM Funded
Z. Yang and Freiwald, W. A., “Joint encoding of facial identity, orientation, gaze, and expression in the middle dorsal face areaSignificance”, Proceedings of the National Academy of Sciences, vol. 118, no. 33, 2021.
CBMM Related
M. Zhang, Badkundri, R., Talbot, M. B., Zawar, R., and Kreiman, G., “Hypothesis-driven Online Video Stream Learning with Augmented Memory”, arXiv, 2021.PDF icon 2104.02206.pdf (2.25 MB)
CBMM Funded
CBMM Memo No.
123
A. Netanyahu, Shu, T., Katz, B., Barbu, A., and Tenenbaum, J. B., “PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception”. 2021.PDF icon CBMM-Memo-123.pdf (3.08 MB)
CBMM Funded
A. Adler, Araya-Polo, M., and Poggio, T., “Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows”, IEEE Signal Processing Magazine, vol. 38, no. 2, pp. 89 - 119, 2021.
CBMM Funded
I. Dasgupta and Gershman, S. J., “Memory as a Computational Resource”, Trends in Cognitive Sciences, vol. 25, no. 3, pp. 240 - 251, 2021.
CBMM Funded
J. Traer, Norman-Haignere, S., and McDermott, J. H., “Causal inference in environmental sound recognition”, Cognition, 2021.
CBMM Funded
CBMM Memo No.
116
O. Kunhardt, Deza, A., and Poggio, T., “The Effects of Image Distribution and Task on Adversarial Robustness”. 2021.PDF icon CBMM_Memo_116.pdf (5.44 MB)
CBMM Funded
S. Anzellottti, Houlihan, S. Dae, Liburd, Jr, S., and Saxe, R., “Leveraging facial expressions and contextual information to investigate opaque representations of emotions.”, Emotion, 2021.PDF icon Anzellotti 2021 Emotion.pdf (1.08 MB)
CBMM Funded
M. A. Cohen, Ostrand, C., Frontero, N., and Pham, P. - N., “Characterizing a snapshot of perceptual experience.”, Journal of Experimental Psychology: General, 2021.
CBMM Funded
G. Kreiman, Biological and Computer Vision. Cambridge, UK: Cambridge University Press, 2021.
CBMM Related
I. Sani, Stemmann, H., Caron, B., Bullock, D., Stemmler, T., Fahle, M., Pestilli, F., and Freiwald, W. A., “The human endogenous attentional control network includes a ventro-temporal cortical node”, Nature Communications, vol. 12, no. 1, 2021.
CBMM Funded
S. Yang, Bill, J., Drugowitsch, J., and Gershman, S. J., “Human visual motion perception shows hallmarks of Bayesian structural inference”, Scientific Reports, vol. 11, no. 1, 2021.
CBMM Funded
CBMM Memo No.
114
T. Poggio, “From Associative Memories to Powerful Machines”. 2021.PDF icon v1.0 (1.01 MB)PDF icon v1.3Section added August 6 on self attention (3.9 MB)
CBMM Funded
W. A. Freiwald and Hosoya, H., “Neuroscience: A Face’s Journey through Space and Time”, Current Biology, vol. 31, no. 1, pp. R13 - R15, 2021.
CBMM Funded
K. Kar and DiCarlo, J. J., “Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition”, Neuron, vol. 109, no. 1, pp. 164 - 176.e5, 2021.
CBMM Funded
T. Pouncy, Tsividis, P., and Gershman, S. J., “What Is the Model in Model‐Based Planning?”, Cognitive Science, vol. 45, no. 1, 2021.
CBMM Funded
T. L. Griffiths and Zaslavsky, N., Encyclopedia of Color Science and TechnologyBayesian Approaches to Color Category Learning. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021, pp. 1 - 5.
CBMM Related
M. S. Tomov, Schulz, E., and Gershman, S. J., “Multi-task reinforcement learning in humans”, Nature Human Behaviour, 2021.
CBMM Funded
S. Valente, Marques, T., and Lima, S. Q., “No evidence for prolactin’s involvement in the post-ejaculatory refractory periodAbstract”, Communications Biology, vol. 4, no. 1, 2021.
CBMM Related
B. Wang and Ponce, C. R., “A Geometric Analysis of Deep Generative Image Models and Its Applications”, in Proc. International Conference on Learning Representations, 2021, 2021.
CBMM Related
J. Zheng, Schjetnan, A. Gómez Pal, Yebra, M., Mosher, C., Kalia, S., Valiante, T. A., Mamelak, A. N., Kreiman, G., and Rutishauser, U., “Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation”, bioRxiv, 2021.
CBMM Related
CBMM Memo No.
131
C. Conwell, Mayo, D., Buice, M. A., Katz, B., Alvarez, G. A., and Barbu, A., “Neural Regression, Representational Similarity, Model Zoology Neural Taskonomy at Scale in Rodent Visual Cortex”. 2021.PDF icon CBMM-Memo-131.pdf (9.37 MB)
CBMM Funded
CBMM Memo No.
130
R. Tejwani, Kuo, Y. - L., Shu, T., Katz, B., and Barbu, A., “Social Interactions as Recursive MDPs”. 2021.PDF icon CBMM-Memo-130.pdf (1.52 MB)
CBMM Funded

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