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2022
Poggio, T. A. How Deep Sparse Networks Avoid the Curse of Dimensionality: Efficiently Computable Functions are Compositionally Sparse. (2022).PDF icon v1.0 (984.15 KB)PDF icon v5.2 more fine tuning (1.14 MB)
Galanti, T. & Galanti, L. On the Implicit Bias Towards Minimal Depth of Deep Neural Networks. arXiv (2022). at <https://arxiv.org/abs/2202.09028>PDF icon 2202.09028.pdf (2 MB)
Tejwani, R. et al. Incorporating Rich Social Interactions Into MDPs. (2022).PDF icon CBMM-Memo-133.pdf (1.68 MB)
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).PDF icon pnas.2121390119.pdf (1.43 MB)
Berrios, W. & Deza, A. Joint rotational invariance and adversarial training of a dual-stream Transformer yields state of the art Brain-Score for Area V4. BrainScore Workshop at COSYNE (2022). at <https://openreview.net/pdf?id=SOulrWP-Xb5>
Zhang, M. et al. Look twice: A generalist computational model predicts return fixations across tasks and species. PLOS Computational Biology 18, e1010654 (2022).PDF icon journal.pcbi_.1010654.pdf (4.51 MB)
Banburski, A. & Rangamani, A. Neural Collapse in Deep Homogeneous Classifiers and the role of Weight Decay. IEEE International Conference on Acoustics, Speech and Signal Processing (2022).
Norman-Haignere, S. V. et al. A neural population selective for song in human auditory cortex. Current Biology (2022). doi:10.1016/j.cub.2022.01.069PDF icon mmc2.pdf (9.52 MB)
Zheng, J. et al. Neurons detect cognitive boundaries to structure episodic memories in humans. Nature Neuroscience 25, 358 - 368 (2022).
Casper, S., Nadeau, M. & Kreiman, G. One thing to fool them all: generating interpretable, universal, and physically-realizable adversarial features. arXiv (2022). doi:10.48550/arXiv.2110.03605PDF icon 2110.03605.pdf (6.7 MB)
Gupte, A., Banburski, A. & Poggio, T. PCA as a defense against some adversaries. (2022).PDF icon CBMM-Memo-135.pdf (2.58 MB)
Houlihan, S. D., Ong, D., Cusimano, M. & Saxe, R. Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind. Proceedings of the 44th Annual Conference of the Cognitive Science Society 44, 854-861 (2022).PDF icon Houlihan 2022 Proceedings of the 44th Annual Conference of the Cognitive Science Society.pdf (687.98 KB)
Anselmi, F. & Poggio, T. Representation Learning in Sensory Cortex: a theory. IEEE Access 1 - 1 (2022). doi:10.1109/ACCESS.2022.3208603PDF icon Representation_Learning_in_Sensory_Cortex_a_theory.pdf (1.17 MB)
Casper, S., Nadeau, M., Hadfield-Menell, D. & Kreiman, G. Robust Feature-Level Adversaries are Interpretability Tools. NeurIPS (2022). at <https://openreview.net/forum?id=lQ--doSB2o>PDF icon 8789_robust_feature_level_adversari.pdf (3.79 MB)
Galanti, T. & Poggio, T. SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks. (2022).PDF icon Implicit Rank Regularization.pdf (1.42 MB)
Shaham, N., Chandra, J., Kreiman, G. & Sompolinsky, H. Stochastic consolidation of lifelong memoryAbstract. Scientific Reports 12, (2022).PDF icon s41598-022-16407-9.pdf (2.54 MB)
Ellis, K., Albright, A., Solar-Lezama, A., Tenenbaum, J. B. & O’Donnell, T. J. Synthesizing theories of human language with Bayesian program inductionAbstract. Nature Communications 13, (2022).PDF icon s41467-022-32012-w.pdf (2.19 MB)
Han, Y., Poggio, T. & Cheung, B. System identification of neural systems: If we got it right, would we know?. (2022).PDF icon CBMM-Memo-136.pdf (1.75 MB)
Xiao, Y. et al. Task-specific neural processes underlying conflict resolution during cognitive control. BioRxiv (2022). doi:10.1101/2022.01.16.476535 PDF icon 2022.01.16.476535v1.full_.pdf (22.96 MB)
Sakai, A. et al. 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)
Kuo, Y. - L. et al. Trajectory Prediction with Linguistic Representations. (2022).PDF icon CBMM-Memo-132.pdf (1.15 MB)
Yamada, M., D'Amario, V., Takemoto, K., Boix, X. & Sasaki, T. Transformer Module Networks for Systematic Generalization in Visual Question Answering. (2022).PDF icon CBMM-Memo-121.pdf (1.06 MB)
Rangamani, A. & Xie, Y. Understanding the Role of Recurrent Connections in Assembly Calculus. (2022).PDF icon CBMM-Memo-137.pdf (1.49 MB)
Kamps, F. S., Richardson, H., N. Murty, A. Ratan, Kanwisher, N. & 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). doi:10.1002/hbm.25815
Madan, S. et al. When and how convolutional neural networks generalize to out-of-distribution category–viewpoint combinations. Nature Machine Intelligence 4, 146 - 153 (2022).

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