Publication

Found 262 results
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2020
Sheskin, M. et al. Online Developmental Science to Foster Innovation, Access, and Impact. Trends in Cognitive Sciences 24, 675 - 678 (2020).
Sheskin, M. et al. Online Developmental Science to Foster Innovation, Access, and Impact. Trends in Cognitive Sciences 24, 675 - 678 (2020).
Poggio, T. & Banburski, A. An Overview of Some Issues in the Theory of Deep Networks. IEEJ Transactions on Electrical and Electronic Engineering 15, 1560 - 1571 (2020).
Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Eventsfor Machine Social Perception. Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020 (2020). at <https://openreview.net/forum?id=_bokm801zhx>PDF icon phase_physically_grounded_abstract_social_events_for_machine_social_perception.pdf (2.49 MB)
Poggio, T., Banburski, A. & Liao, Q. Theoretical issues in deep networks. Proceedings of the National Academy of Sciences 201907369 (2020). doi:10.1073/pnas.1907369117PDF icon PNASlast.pdf (915.3 KB)
Gen, C. et al. ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. arXiv (2020). at <https://arxiv.org/abs/2007.04954>PDF icon 2007.04954.pdf (7.06 MB)
Gen, C. et al. ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. arXiv (2020). at <https://arxiv.org/abs/2007.04954>PDF icon 2007.04954.pdf (7.06 MB)
Schwartz, J. et al. ThreeDWorld (TDW): A High-Fidelity, Multi-Modal Platform for Interactive Physical Simulation. (2020). at <http://www.threedworld.org/>
Schwartz, J. et al. ThreeDWorld (TDW): A High-Fidelity, Multi-Modal Platform for Interactive Physical Simulation. (2020). at <http://www.threedworld.org/>
Ben-Yosef, G., Kreiman, G. & Ullman, S. What can human minimal videos tell us about dynamic recognition models?. International Conference on Learning Representations (ICLR 2020) (2020). at <https://baicsworkshop.github.io/pdf/BAICS_1.pdf>PDF icon Authors' final version (516.09 KB)
2021
Shu, T. et al. AGENT: A Benchmark for Core Psychological Reasoning. Proceedings of the 38th International Conference on Machine Learning (2021).
Baidya, A., Dapello, J., DiCarlo, J. J. & Marques, T. Combining Different V1 Brain Model Variants to Improve Robustness to Image Corruptions in CNNs. NeurIPS 2021 (2021). at <https://nips.cc/Conferences/2021/ScheduleMultitrack?event=41268>
Kuo, Y. - L., Katz, B. & Barbu, A. Compositional Networks Enable Systematic Generalization for Grounded Language Understanding. (2021).PDF icon CBMM-Memo-129.pdf (1.2 MB)
Kuo, Y. - L., Barbu, A. & Katz, B. Compositional RL Agents That Follow Language Commands in Temporal Logic. (2021).PDF icon CBMM-Memo-127.pdf (2.12 MB)
Kuo, Y. - L., Katz, B. & Barbu, A. Compositional RL Agents That Follow Language Commands in Temporal Logic. Frontiers in Robotics and AI 8, (2021).PDF icon frobt-08-689550.pdf (1.57 MB)
N. Murty, A. Ratan, Bashivan, P., Abate, A., DiCarlo, J. J. & Kanwisher, N. Computational models of category-selective brain regions enable high-throughput tests of selectivity. Nature Communications 12, (2021).PDF icon s41467-021-25409-6.pdf (6.47 MB)
Banburski, A., De La Torre, F., Pant, N., Shastri, I. & Poggio, T. Distribution of Classification Margins: Are All Data Equal?. (2021).PDF icon CBMM Memo 115.pdf (9.56 MB)PDF icon arXiv version (23.05 MB)
Xu, M. et al. Dynamics and Neural Collapse in Deep Classifiers trained with the Square Loss. (2021).PDF icon v1.0 (4.61 MB)PDF icon v1.4corrections to generalization section (5.85 MB)PDF icon v1.7Small edits (22.65 MB)
Gant, J., Banburski, A., Deza, A. & Poggio, T. Evaluating the Adversarial Robustness of a Foveated Texture Transform Module in a CNN. NeurIPS 2021 (2021). at <https://nips.cc/Conferences/2021/Schedule?showEvent=21868>
Yang, C. et al. Evolutionary and biomedical insights from a marmoset diploid genome assembly. Nature (2021). doi:10.1038/s41586-021-03535-x
Yang, C. et al. Evolutionary and biomedical insights from a marmoset diploid genome assembly. Nature (2021). doi:10.1038/s41586-021-03535-x
Yang, C. et al. Evolutionary and biomedical insights from a marmoset diploid genome assembly. Nature (2021). doi:10.1038/s41586-021-03535-x
Yang, C. et al. Evolutionary and biomedical insights from a marmoset diploid genome assembly. Nature (2021). doi:10.1038/s41586-021-03535-x
McNamee, D., Stachenfeld, K., Botvinick, M. M. & Gershman, S. J. Flexible modulation of sequence generation in the entorhinal-hippocampal system. Nature Neuroscience (2021). doi:10.1038/s41593-021-00831-7
Casper, S. et al. Frivolous Units: Wider Networks Are Not Really That Wide. AAAI 2021 (2021). at <https://dblp.org/rec/conf/aaai/CasperBDGSVK21.html>PDF icon 1912.04783.pdf (6.69 MB)

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