Publication

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2022
Tejwani, R. et al. Incorporating Rich Social Interactions Into MDPs. 2022 IEEE International Conference on Robotics and Automation (ICRA)2022 International Conference on Robotics and Automation (ICRA) (2022). doi:10.1109/ICRA46639.2022.9811991
Tejwani, R. et al. Incorporating Rich Social Interactions Into MDPs. (2022).PDF icon CBMM-Memo-133.pdf (1.68 MB)
Pouncy, T. & Gershman, S. J. Inductive biases in theory-based reinforcement learning. Cognitive Psychology 138, 101509 (2022).
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)
Pramod, R. T., Cohen, M. A., Tenenbaum, J. B. & Kanwisher, N. Invariant representation of physical stability in the human brain. eLife 11, (2022).
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>
Letizia, M. et al. Learning new physics efficiently with nonparametric methodsAbstract. The European Physical Journal C 82, (2022).
Xu, C. et al. Lecture Notes in Computer ScienceComputer Vision – ECCV 2022Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models. 13697, 638 - 656 (Springer Nature Switzerland, 2022).
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)
Gershman, S. J. & Burke, T. Mental control of uncertainty. Cognitive, Affective, & Behavioral Neuroscience 23, 465 - 475 (2022).
Zhou, L., Smith, K., Tenenbaum, J. B. & Gerstenberg, T. Mental Jenga: A counterfactual simulation model of causal judgments about physical support. PsyArXiv (2022). at <https://psyarxiv.com/4a5uh>
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)
Meyers, E. M. NeuroDecodeR: A package for neural decoding analyses in R. bioRxiv (2022). at <https://www.biorxiv.org/content/10.1101/2022.12.17.520811v1>
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)
Bagus, A. Marliawaty, Marques, T., Sanghavi, S., DiCarlo, J. J. & Schrimpf, M. Primate Inferotemporal Cortex Neurons Generalize Better to Novel Image Distributions Than Analogous Deep Neural Networks Units. NeurIPS (2022). at <https://openreview.net/forum?id=iPF7mhoWkOl>
Quality Early Learning: Nurturing Children's Potential. (The World Bank, 2022). doi:10.1596/978-1-4648-1795-3
Cheng, E. et al. Quantifying the Emergence of Symbolic Communication. CogSci (2022). at <https://escholarship.org/uc/item/08n3293v>
Houlihan, S. Dae, Ong, D., Cusimano, M. & Saxe, R. Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind. Proceedings of the 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)
Montagna, F., Noceti, N., Rosasco, L., Zhang, K. & Locatello, F. Scalable Causal Discovery with Score Matching. NeurIPS 2022 (2022). at <https://openreview.net/forum?id=v56PHv_W2A>
Galanti, T. & Poggio, T. SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks. (2022).PDF icon Implicit Rank Minimization.pdf (1.76 MB)

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