All Publications

2023

U. Singhal, Cheung, B., Chandra, K., Ragan-Kelley, J., Tenenbaum, J. B., Poggio, T., and Yu, S. X., “How to Guess a Gradient”, arXiv, 2023.
CBMM Funded
G. Tuckute, Feather, J., Boebinger, D., and McDermott, J. H., “Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions”, PLOS Biology, vol. 21, no. 12, p. e3002366, 2023.
CBMM Funded
Y. Xiang, Landy, J., Cushman, F. A., Vélez, N., and Gershman, S. J., “Actual and counterfactual effort contribute to responsibility attributions in collaborative tasks”, Cognition, vol. 241, p. 105609, 2023.
CBMM Funded
C. Yu, Burgess, N., Sahani, M., and Gershman, S. J., “Successor-Predecessor Intrinsic Exploration”, in Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023.
CBMM Funded
Z. M. Aghajan, Kreiman, G., and Fried, I., “Minute-scale periodicity of neuronal firing in the human entorhinal cortex”, Cell Reports, vol. 42, no. 11, p. 113271, 2023.PDF icon 1-s2.0-S2211124723012834-main.pdf (5.33 MB)
CBMM Funded
E. Caldarelli, Chatalic, A., Colom´e, A. `a, Rosasco, L., and Torras, C., “Heteroscedastic Gaussian Processes and Random Features: Scalable Motion Primitives with Guarantees”, in 7th Conference on Robot Learning (CoRL 2023, Altanta, GA, 2023.
CBMM Funded
A. Duan, Batzianoulis, I., Camoriano, R., Rosasco, L., Pucci, D., and Billard, A., “A structured prediction approach for robot imitation learning”, The International Journal of Robotics Research, vol. 43, no. 2, pp. 113 - 133, 2023.
CBMM Related
I. Yildirim, Siegel, M. H., Soltani, A. A., Chaudhuri, S. Ray, and Tenenbaum, J. B., “Perception of 3D shape integrates intuitive physics and analysis-by-synthesis”, Nature Human Behaviour, 2023.
CBMM Funded
J. Feather, Leclerc, G., Mądry, A., and McDermott, J. H., “Model metamers reveal divergent invariances between biological and artificial neural networks”, Nature Neuroscience, 2023.
CBMM Funded
G. Gaziv, Lee, M. J., and DiCarlo, J. J., “Robustified ANNs Reveal Wormholes Between Human Category Percepts”, arXiv, 2023.
CBMM Funded
T. Poggio and Magrini, M., Cervelli menti algoritmi. Sperling & Kupfer, 2023, p. 272.
CBMM Funded
L. Schiatti, Gori, M., Schrimpf, M., Cappagli, G., Morelli, F., Signorini, S., Katz, B., and Barbu, A., “Modeling Visual Impairments with Artificial Neural Networks: a Review”, in International Conference on Computer Vision 2023, Paris, 2023.
CBMM Funded
P. Singh, Li, Y., Sikarwar, A., Lei, S. Weixian, Gao, D., Talbot, M. B., Sun, Y., Shou, M. Zheng, Kreiman, G., and Zhang, M., “ Learning to Learn: How to Continuously Teach Humans and Machines ”, in International Conference on Computer Vision (ICCV), 2023, Paris, France, 2023.
CBMM Funded
C. Vega, Molinari, C., Rosasco, L., and Villa, S., “Fast iterative regularization by reusing dataAbstract”, Journal of Inverse and Ill-posed Problems, 2023.
CBMM Funded
CBMM Memo No.
143
Y. Gan and Poggio, T., “A Homogeneous Transformer Architecture”. 2023.PDF icon CBMM Memo 143 v2 (1.1 MB)
CBMM Funded
E. J. Bigelow, McCoy, J. P., and Ullman, T. D., “Non-commitment in mental imagery”, Cognition, vol. 238, p. 105498, 2023.
CBMM Funded
P. A. Feliciano-Ramos, Galazo, M., Penagos, H., and Wilson, M., “Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices”, Learning & Memory, vol. 30, no. 9, pp. 221 - 236, 2023.
CBMM Related
T. P. O'Connell, Bonnen, T., Friedman, Y., Tewari, A., Tenenbaum, J. B., Sitzmann, V., and Kanwisher, N., “Approaching human 3D shape perception with neurally mappable models”, arXiv, 2023.
CBMM Funded
T. Bricken, Schaeffer, R., Olshausen, B., and Kreiman, G., “Emergence of Sparse Representations from Noise”, ICML 2023. Honolulu, HI, 2023.
CBMM Funded
C. Consortium, Ferrante, O., Gorska-Klimowska, U., Henin, S., Hirschhorn, R., Khalaf, A., Lepauvre, A., Liu, L., Richter, D., Vidal, Y., Bonacchi, N., Brown, T., Sripad, P., Armendariz, M., Bendtz, K., Ghafari, T., Hetenyi, D., Jeschke, J., Kozma, C., Mazumder, D. R., Montenegro, S., Seedat, A., Sharafeldin, A., Yang, S., Baillet, S., Chalmers, D. J., Cichy, R. M., Fallon, F., Panagiotaropoulos, T. I., Blumenfeld, H., de Lange, F. P., Devore, S., Jensen, O., Kreiman, G., Luo, H., Boly, M., Dehaene, S., Koch, C., Tononi, G., Pitts, M., Mudrik, L., and Melloni, L., “An adversarial collaboration to critically evaluate theories of consciousness”, bioRxiv, 2023.
CBMM Related
K. Dobs, Yuan, J., Martinez, J., and Kanwisher, N., “Behavioral signatures of face perception emerge in deep neural networks optimized for face recognition”, Proceedings of the National Academy of Sciences, vol. 120, no. 32, 2023.
CBMM Funded
Y. Han, Poggio, T., and 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, vol. 202. pp. 12430-12444, 2023.PDF icon han23d.pdf (797.48 KB)
CBMM Funded
S. Dae Houlihan, Kleiman-Weiner, M., Hewitt, L. B., Tenenbaum, J. B., and Saxe, R., “Emotion prediction as computation over a generative theory of mind”, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 381, no. 2251, 2023.PDF icon houlihan2023computedappraisals.pdf (2.37 MB)
CBMM Funded
X. Puig, Shu, T., Tenenbaum, J. B., and Torralba, A., “NOPA: Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistants”, in 2023 IEEE International Conference on Robotics and Automation (ICRA), London, United Kingdom, 2023.
CBMM Related
CBMM Memo No.
142
Y. Xie, Li, Y., and Rangamani, A., “Skip Connections Increase the Capacity of Associative Memories in Variable Binding Mechanisms”. 2023.PDF icon CBMM-Memo-142.pdf (1.64 MB)
CBMM Funded

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