All Publications

2022

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
L. Zhou, Smith, K., Tenenbaum, J. B., and Gerstenberg, T., “Mental Jenga: A counterfactual simulation model of causal judgments about physical support”, PsyArXiv, 2022.
CBMM Related
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
M. Bendini and Devercelli, A., Eds., Quality Early Learning: Nurturing Children's Potential. The World Bank, 2022.
CBMM Related
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
E. Cheng, Kuo, Y. - L., Correa, J., Katz, B., Cases, I., and Barbu, A., “Quantifying the Emergence of Symbolic Communication”, CogSci, 2022.
CBMM Related
E. Cheng, Kuo, Y. - L., Cases, I., Katz, B., and Barbu, A., “Spontaneous sign emergence in humans and machines through an embodied communication game”, in JCoLE Workshop, 2022.
CBMM Related
A. Harrington and Deza, A., “Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks”, International Conference on Learning Representations (ICLR). 2022.
CBMM Funded
Y. - L. Kuo, Huang, X., Barbu, A., McGill, S. G., Katz, B., Leonard, J. J., and Rosman, G., “Trajectory Prediction with Linguistic Representations”, in 2022 IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, PA, USA, 2022.
CBMM Funded
B. Woo and Spelke, E., “Eight-Month-Old Infants’ Social Evaluations of Agents Who Act on False Beliefs”, Proceedings of the Annual Meeting of the Cognitive Science Society, vol. 44, 2022.
CBMM Funded
A. Yaari, DeWitt, J., Hu, H., Stankovits, B., Felshin, S., Berzak, Y., Aparicio, H., Katz, B., Cases, I., and Barbu, A., “The Aligned Multimodal Movie Treebank: An audio, video, dependency-parse treebank”, in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022.
CBMM Related

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