All Publications

2022

A. Banburski and Rangamani, A., “Neural Collapse in Deep Homogeneous Classifiers and the role of Weight Decay”, in IEEE International Conference on Acoustics, Speech and Signal Processing, Singapore, 2022.
CBMM Funded
A. J. Thomas, Saxe, R., and 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, vol. 119, no. 32, 2022.PDF icon pnas.2121390119.pdf (1.43 MB)
CBMM Funded
K. Dobs, Martinez-Trujillo, J., Kell, A. J. E., and Kanwisher, N., “Brain-like functional specialization emerges spontaneously in deep neural networks”, Science Advances, vol. 8, no. 11, 2022.
CBMM Funded
CBMM Memo No.
134
T. Galanti and Poggio, T., “SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks”. 2022.PDF icon Implicit Rank Regularization.pdf (1.42 MB)
CBMM Funded
T. Galanti and Galanti, L., “On the Implicit Bias Towards Minimal Depth of Deep Neural Networks”, arXiv, 2022.PDF icon 2202.09028.pdf (2 MB)
CBMM Funded
F. S. Kamps, Richardson, H., N. Murty, A. Ratan, Kanwisher, N., and Saxe, R., “Using child‐friendly movie stimuli to study the development of face, place, and object regions from age 3 to 12 years”, Human Brain Mapping, 2022.
CBMM Related
Y. Li, Wang, Y. Q., Boger, T., Smith, K. A., Gershman, S. J., and Ullman, T., “An approximate representation of objects underlies physical reasoning”, psyArXiv, 2022.
CBMM Related
J. Zheng, Schjetnan, A. G. P., Yebra, M., Gomes, B. A., Mosher, C. P., Kalia, S. K., Valiante, T. A., Mamelak, A. N., Kreiman, G., and Rutishauser, U., “Neurons detect cognitive boundaries to structure episodic memories in humans”, Nature Neuroscience, vol. 25, no. 3, pp. 358 - 368, 2022.
CBMM Funded
CBMM Memo No.
121
M. Yamada, D'Amario, V., Takemoto, K., Boix, X., and Sasaki, T., “Transformer Module Networks for Systematic Generalization in Visual Question Answering”. 2022.PDF icon CBMM-Memo-121.pdf (1.06 MB)PDF icon version 2 (3/22/2023) (1.33 MB)
CBMM Funded
M. Armendariz, Xiao, W., Vinken, K., and Kreiman, G., “Do computational models of vision need shape-based representations? Evidence from an individual with intriguing visual perceptions”, Cognitive Neuropsychology, pp. 1 - 3, 2022.
CBMM Funded
A. Bardon, Xiao, W., Ponce, C. R., Livingstone, M. S., and Kreiman, G., “Face neurons encode nonsemantic features”, Proceedings of the National Academy of Sciences, vol. 119, no. 16, 2022.
CBMM Funded
S. Madan, Henry, T., Dozier, J., Ho, H., Bhandari, N., Sasaki, T., Durand, F., Pfister, H., and Boix, X., “When and how convolutional neural networks generalize to out-of-distribution category–viewpoint combinations”, Nature Machine Intelligence, vol. 4, no. 2, pp. 146 - 153, 2022.
CBMM Funded
S. V. Norman-Haignere, Feather, J., Boebinger, D., Brunner, P., Ritaccio, A., McDermott, J. H., Schalk, G., and Kanwisher, N., “A neural population selective for song in human auditory cortex”, Current Biology, 2022.PDF icon mmc2.pdf (9.52 MB)
CBMM Funded
CBMM Memo No.
119
A. Sakai, Sunagawa, T., Madan, S., Suzuki, K., Katoh, T., Kobashi, H., Pfister, H., Sinha, P., Boix, X., and Sasaki, T., “Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations”. 2022.PDF icon CBMM-Memo-119.pdf (31.08 MB)
CBMM Funded
L. A. Becker, Penagos, H., Flores, F. J., Manoach, D. S., Wilson, M. A., and Varela, C., “Eszopiclone and Zolpidem Produce Opposite Effects on Hippocampal Ripple DensityDataSheet1.docx”, Frontiers in Pharmacology, vol. 12, 2022.
CBMM Funded
S. Casper, Nadeau, M., and Kreiman, G., “One thing to fool them all: generating interpretable, universal, and physically-realizable adversarial features”, arXiv, 2022.PDF icon 2110.03605.pdf (6.7 MB)
CBMM Funded
A. Francl and McDermott, J. H., “Deep neural network models of sound localization reveal how perception is adapted to real-world environments”, Nature Human Behavior, vol. 6, pp. 111–133 , 2022.PDF icon s41562-021-01244-z.pdf (7.22 MB)
CBMM Funded
M. J. McPherson, Grace, R. C., and McDermott, J. H., “Harmonicity aids hearing in noise”, Attention, Perception, & Psychophysics, 2022.
CBMM Related
A. Sikarwar and Kreiman, G., “On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering”, arXiv, 2022.PDF icon On_the_Efficacy_of_Co-Attention_Transformer_Layers.pdf (35.54 MB)
CBMM Funded
A. J. Thomas, Woo, B., Nettle, D., Spelke, E. S., and Saxe, R., “Early concepts of intimacy: Young humans use saliva sharing to infer close relationships”, Science, vol. 375, no. 6578, pp. 311 - 315, 2022.
CBMM Funded
Y. Xiao, Chou, C. - C., Cosgrove, G. Rees, Crone, N. E., Stone, S., Madsen, J. R., Reucroft, I., Shih, Y. - C., Weisholtz, D., Yu, H. - Y., Anderson, W. S., and Kreiman, G., “Task-specific neural processes underlying conflict resolution during cognitive control”, BioRxiv, 2022.PDF icon 2022.01.16.476535v1.full_.pdf (22.96 MB)
CBMM Funded
CBMM Memo No.
135
A. Gupte, Banburski, A., and Poggio, T., “PCA as a defense against some adversaries”. 2022.PDF icon CBMM-Memo-135.pdf (2.58 MB)
CBMM Funded
CBMM Memo No.
133
R. Tejwani, Kuo, Y. - L., Shu, T., Stankovits, B., Gutfreund, D., Tenenbaum, J. B., Katz, B., and Barbu, A., “Incorporating Rich Social Interactions Into MDPs”. 2022.PDF icon CBMM-Memo-133.pdf (1.68 MB)
CBMM Funded
CBMM Memo No.
132
Y. - L. Kuo, Huang, X., Barbu, A., McGill, S. G., Katz, B., Leonard, J. J., and Rosman, G., “Trajectory Prediction with Linguistic Representations”. 2022.PDF icon CBMM-Memo-132.pdf (1.15 MB)
CBMM Funded
W. Berrios and Deza, A., “Joint rotational invariance and adversarial training of a dual-stream Transformer yields state of the art Brain-Score for Area V4”, in BrainScore Workshop at COSYNE, 2022.
CBMM Funded

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