Publications

CBMM Memos were established in 2014 as a mechanism for our center to share research results with the wider scientific community. Click here to read more about the memos and to see a full list of the memos.

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Thomas, A. J., Saxe, R. & Spelke, E. S. Infants infer potential social partners by observing the interactions of their parent with unknown others. Proceedings of the National Academy of Sciences 119, (2022).

pnas.2121390119.pdf (1.43 MB)

Leonard, J. A., Lee, Y. & Schulz, L. Infants make more attempts to achieve a goal when they see adults persist. Science 357, 1290 - 1294 (2017).

Spokes, A. C. Infants’ Reasoning about Affiliation and Caregiving. Cognitive Development Society (CDS) Biennial Meeting (2015).

Spokes, A. C. Infants’ Reasoning about Affiliation and Caregiving. Cognitive Development Society (CDS) | More on Development workshop (2015).

Thomas, A. J., Saxe, R. & Spelke, E. S. Infants represent 'like-kin' affiliation . Budapest Conference on Cognitive Development (2020).

Dillon, M. R., Izard, V. & Spelke, E. S. Infants’ sensitivity to shape changes. Cognitive Development Society Pre-Conference on the Development of Spatial Thinking (2015).

Dillon, M. R., Izard, V. & Spelke, E. S. Infants’ sensitivity to shape changes in 2D visual forms. Infancy 25, 618 - 639 (2020).

Rajalingham, R., Kar, K., Sanghavi, S., Dehaene, S. & DiCarlo, J. J. The inferior temporal cortex is a potential cortical precursor of orthographic processing in untrained monkeys. Nature Communications 11, (2020).

s41467-020-17714-3.pdf (25.01 MB)

Wu, Y. & Schulz, L. Inferring Beliefs and Desires From Emotional Reactions to Anticipated and Observed Events. Child Development (2017). doi:10.1111/cdev.12759

Wu_et_al-2017-Child_Development.pdf (883.1 KB)

Inferring mass in complex scenes by mental simulation. (2016).

Linderman, S. W., Adams, R. & Pillow, J. Inferring structured connectivity from spike trains under negative-binomial generalized linear models. (2015).

cosyne2015a.pdf (384.83 KB)

Tsividis, P., Gershman, S. J., Tenenbaum, J. B. & Schulz, L. Information Selection in Noisy Environments with Large Action Spaces. 9th Biennial Conference of the Cognitive Development Society Columbus, OH, (2015).

Allen, K., Yildirim, I. & Tenenbaum, J. B. Integrating Identification and Perception: A case study of familiar and unfamiliar face processing. Proceedings of the Thirty-Eight Annual Conference of the Cognitive Science Society (2016).

allen_5_13.pdf (2.13 MB)

Schrimpf, M. et al. Integrative Benchmarking to Advance Neurally Mechanistic Models of Human Intelligence. Neuron 108, 413 - 423 (2020).

Yildirim, I., Wu, J., Kanwisher, N. & Tenenbaum, J. B. An integrative computational architecture for object-driven cortex. Current Opinion in Neurobiology 55, 73 - 81 (2019).

Meyers, E., Borzello, M., Freiwald, W. A. & Tsao, D. Intelligent Information Loss: The Coding of Facial Identity, Head Pose, and Non-Face Information in the Macaque Face Patch System. The Journal of Neuroscience 35, (2015).

Bach, F. & Poggio, T. Introduction Special issue: Deep learning. Information and Inference 5, 103-104 (2016).

Gerstenberg, T. & Tenenbaum, J. B. Oxford Handbook of Causal Reasoning (Oxford University Press, 2016).

Intuitive Theories (Gerstenberg, Tenenbaum, 2016.pdf (6.06 MB)

Anselmi, F., Rosasco, L. & Poggio, T. On invariance and selectivity in representation learning. Information and Inference: A Journal of the IMA iaw009 (2016). doi:10.1093/imaiai/iaw009

imaiai.iaw009.full_.pdf (267.87 KB)

Anselmi, F., Rosasco, L. & Poggio, T. On Invariance and Selectivity in Representation Learning. (2015).

CBMM Memo No. 029 (812.07 KB)

Leibo, J. Z., Liao, Q., Anselmi, F. & Poggio, T. The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. (2015).

modularity_dataset_ver1.tar.gz (36.14 MB)

Leibo, J. Z., Liao, Q., Anselmi, F. & Poggio, T. The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. PLOS Computational Biology 11, e1004390 (2015).

journal.pcbi_.1004390.pdf (2.04 MB)

Leibo, J. Z., Liao, Q., Anselmi, F. & Poggio, T. The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. (2014). doi:10.1101/004473

CBMM Memo 004_new.pdf (2.25 MB)

Kell, A. J. E. & McDermott, J. H. Invariance to background noise as a signature of non-primary auditory cortex. Nature Communications 10, (2019).

Tacchetti, A., Isik, L. & Poggio, T. Invariant action recognition dataset. (2017). at <https://doi.org/10.7910/DVN/DMT0PG>

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