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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D

Banburski, A., De La Torre, F., Pant, N., Shastri, I. & Poggio, T. Distribution of Classification Margins: Are All Data Equal?. (2021).

CBMM Memo 115.pdf (9.56 MB)

arXiv version (23.05 MB)

Norman-Haignere, S. V., Kanwisher, N., McDermott, J. H. & Conway, B. R. Divergence in the functional organization of human and macaque auditory cortex revealed by fMRI responses to harmonic tones. Nature Neuroscience (2019). doi:10.1038/s41593-019-0410-7

Armendariz, M., Xiao, W., Vinken, K. & Kreiman, G. Do computational models of vision need shape-based representations? Evidence from an individual with intriguing visual perceptions. Cognitive Neuropsychology 1 - 3 (2022). doi:10.1080/02643294.2022.2041588

Volokitin, A., Roig, G. & Poggio, T. Do Deep Neural Networks Suffer from Crowding?. (2017).

CBMM-Memo-069.pdf (6.47 MB)

Volokitin, A. & Roig, G. Do Deep Neural Networks Suffer from Crowding? [code]. (2017).

Villalobos, K. M. et al. Do Neural Networks for Segmentation Understand Insideness?. (2020).

CBMM-Memo-105.pdf (4.63 MB)

CBMM Memo 105 v2 (July 2, 2020) (3.2 MB)

CBMM Memo 105 v3 (January 25, 2022) (8.33 MB)

Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Do You See What I Mean? Visual Resolution of Linguistic Ambiguities. (2016).

memo-51.pdf (2.74 MB)

Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Do You See What I Mean? Visual Resolution of Linguistic Ambiguities. Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal. (2015).

Wang, P. & Yuille, A. DOC: Deep OCclusion Recovering From A Single Image. ECCV (2016).

Kryven, M., Scholl, B. & Tenenbaum, J. B. Does intuitive inference of physical stability interruptattention?. Cognitive Sciences Society (2019).

Poggio, T., Kur, G. & Banburski, A. Double descent in the condition number. (2019).

Fixing typos, clarifying error in y, best approach is crossvalidation (837.18 KB)

Incorporated footnote in text plus other edits (854.05 KB)

Deleted previous discussion on kernel regression and deep nets: it will appear, extended, in a separate paper (795.28 KB)

correcting a bad typo (261.24 KB)

Deleted plot of condition number of kernel matrix: we cannot get a double descent curve (769.32 KB)

Ullman, T. D. et al. Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects. Cognitive Science Society (2019). at <https://mindmodeling.org/cogsci2019/papers/0506/index.html>

Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects.pdf (2.62 MB)

Banburski, A. et al. Dreaming with ARC. Learning Meets Combinatorial Algorithms workshop at NeurIPS 2020 (2020).

CBMM Memo 113.pdf (1019.64 KB)

Dehghani, N. Dynamic balance of excitation and inhibition in human and monkey neocortex. Nature Scientific Reports (2016). doi:10.1038/srep23176

BalanceExcitationInhibition.pdf (2.1 MB)

Meyers, E. Dynamic population coding and its relationship to working memory. Journal of Neurophysiology 120, 2260 - 2268 (2018).

Xu, M. et al. Dynamics and Neural Collapse in Deep Classifiers trained with the Square Loss. (2021).

v1.0 (4.61 MB)

v1.4corrections to generalization section (5.85 MB)

v1.7Small edits (22.65 MB)

Banburski, A. et al. Dynamics & Generalization in Deep Networks -Minimizing the Norm. NAS Sackler Colloquium on Science of Deep Learning (2019).

Xu, M., Rangamani, A., Liao, Q., Galanti, T. & Poggio, T. Dynamics in Deep Classifiers trained with the Square Loss: normalization, low rank, neural collapse and generalization bounds. Research (2023). doi:10.34133/research.0024

research.0024.pdf (4.05 MB)

N. Murty, A. Ratan & Arun, S. P. Dynamics of 3D view invariance in monkey inferotemporal cortex. Journal of Neurophysiology 11319212373232821, 2180 - 2194 (2015).

Isik, L., Meyers, E., Leibo, J. Z. & Poggio, T. The dynamics of invariant object recognition in the human visual system. J Neurophysiol 111, 91-102 (2014).

Isik, L., Meyers, E., Leibo, J. Z. & Poggio, T. The dynamics of invariant object recognition in the human visual system. (2014). doi:http://dx.doi.org/10.7910/DVN/KRUPXZ

Stern, M., Sompolinsky, H. & Abbott, L. F. Dynamics of random neural networks with bistable units. Phys Rev E Stat Nonlin Soft Matter Phys 90, (2014).

E

Thomas, A. J., Woo, B., Nettle, D., Spelke, E. S. & Saxe, R. Early concepts of intimacy: Young humans use saliva sharing to infer close relationships. Science 375, 311 - 315 (2022).

Spokes, A. C. & Spelke, E. S. Early Reasoning about Affiliation and Caregiving. Cognitive Development Society (CDS) (2015).

Spokes, A. C. & Spelke, E. S. Early reasoning about affiliation and kinship. (2015).

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