Publications

CBMM Memos were established in 2014 as a mechanism for our center to share research results with the wider scientific community. Click here to read more about the memos and to see a full list of the memos.

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Vélez, N., Chen, A. M., Burke, T., Cushman, F. A. & Gershman, S. J. Teachers recruit mentalizing regions to represent learners’ beliefs. Proceedings of the National Academy of Sciences 120, (2023).

Xiao, Y. et al. Task-specific neural processes underlying conflict resolution during cognitive control. BioRxiv (2022). doi:10.1101/2022.01.16.476535

2022.01.16.476535v1.full_.pdf (22.96 MB)

Kell, A. J. E., Yamins, D. L. K., Shook, E. N., Norman-Haignere, S. V. & McDermott, J. H. A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy. Neuron 98, (2018).

S

Han, Y., Poggio, T. & Cheung, B. System Identification of Neural Systems: If We Got It Right, Would We Know?. Proceedings of the 40th International Conference on Machine Learning, PMLR 202, 12430-12444 (2023).

han23d.pdf (797.48 KB)

Han, Y., Poggio, T. & Cheung, B. System identification of neural systems: If we got it right, would we know?. (2022).

CBMM-Memo-136.pdf (1.75 MB)

Garrote, E. et al. System for Mouse Behavior Recognition. (2010).

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).

s41467-022-32012-w.pdf (2.19 MB)

Soltani, A. Arsalan, Huang, H., Wu, J., Kulkarni, T. & Tenenbaum, J. B. Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017). doi:10.1109/CVPR.2017.269

Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks.pdf (2.86 MB)

Anselmi, F., Evangelopoulos, G., Rosasco, L. & Poggio, T. Symmetry Regularization. (2017).

CBMM-Memo-063.pdf (6.1 MB)

Leavitt, M. L., Mendoza-Halliday, D. & J.C., M. - T. Sustained Activity Encoding Working Memories: Not Fully Distributed. Trends in Neurosciences 40 , 328-346 (2017).

Yu, C., Burgess, N., Sahani, M. & Gershman, S. J. Successor-Predecessor Intrinsic Exploration. Advances in Neural Information Processing Systems 36 (NeurIPS 2023) (2023). at <https://proceedings.neurips.cc/paper_files/paper/2023/hash/e6f2b968c4ee8ba260cd7077e39590dd-Abstract-Conference.html>

Leibo, J. Z., Liao, Q. & Poggio, T. Subtasks of unconstrained face recognition. (2014).

Leibo, J. Z., Liao, Q. & Poggio, T. Subtasks of Unconstrained Face Recognition. (2014).

Leibo_Liao_Poggio_subtasks_VISAPP_2014.pdf (268.69 KB)

Duan, A. et al. A structured prediction approach for robot imitation learning. The International Journal of Robotics Research 43, 113 - 133 (2023).

Lewis, O. Structured learning and inference with neural networks and generative models. (2018).

Gershman, S. J. & Cikara, M. Structure learning principles of stereotype change. Psychonomic Bulletin & Review 30, 1273 - 1293 (2023).

Gaziv, G., Lee, M. J. & DiCarlo, J. J. Strong and Precise Modulation of Human Percepts via Robustified ANNs. NeurIPS 2023 (2023). at <https://proceedings.neurips.cc/paper_files/paper/2023/hash/d00904cebc0d5b69fada8ad33d0f1422-Abstract-Conference.html>

Liao, Q., Kawaguchi, K. & Poggio, T. Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning. (2016).

CBMM-Memo-057.pdf (1.27 MB)

Bergen, L. & Goodman, N. D. The strategic use of noise in pragmatic reasoning. (2014).

Shaham, N., Chandra, J., Kreiman, G. & Sompolinsky, H. Stochastic consolidation of lifelong memoryAbstract. Scientific Reports 12, (2022).

s41598-022-16407-9.pdf (2.54 MB)

Traer, J. & McDermott, J. H. Statistics of natural reverberation enable perceptual separation of sound and space. Proceedings of the National Academy of Sciences 113, E7856 - E7865 (2016).

Hart, Y. et al. The statistical shape of geometric reasoning. Scientific Reports 8, (2018).

Poggio, T. Stable Foundations for Learning: a framework for learning theory (in both the classical and modern regime). (2020).

Original file (584.54 KB)

Corrected typos and details of "equivalence" CV stability and expected error for interpolating machines. Added Appendix on SGD. (905.29 KB)

Edited Appendix on SGD. (909.19 KB)

Deleted Appendix. Corrected typos etc (880.27 KB)

Added result about square loss and min norm (898.03 KB)

Cheng, E., Kuo, Y. - L., Cases, I., Katz, B. & Barbu, A. Spontaneous sign emergence in humans and machines through an embodied communication game. JCoLE Workshop (2022).

Palmer, I., Rouditchenko, A., Barbu, A., Katz, B. & Glass, J. Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset. Interspeech 2021 (2021). doi:10.21437/Interspeech.2021

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