All Publications

2024

E. M. Meyers, “NeuroDecodeR: a package for neural decoding in RData_Sheet_1.docx”, Frontiers in Neuroinformatics, vol. 17, 2024.
CBMM Funded
B. Peters, DiCarlo, J. J., Gureckis, T., Haefner, R., Isik, L., Tenenbaum, J., Konkle, T., Naselaris, T., Stachenfeld, K., Tavares, Z., Tsao, D., Yildirim, I., and Kriegeskorte, N., “How does the primate brain combine generative and discriminative computations in vision?”, arXiv, 2024.

2023

CBMM Memo No.
144
M. Xu, Galanti, T., Rangamani, A., Rosasco, L., Pinto, A., and Poggio, T., “The Janus effects of SGD vs GD: high noise and low rank”. 2023.PDF icon Updated with appendix showing empirically that the main results extend to deep nonlinear networks (2.95 MB)PDF icon Small updates...typos... (616.82 KB)
CBMM Funded
K. R. Allen, Smith, K. A., Bird, L. - A., Tenenbaum, J. B., Makin, T. R., and Cowie, D., “Lifelong learning of cognitive styles for physical problem-solving: The effect of embodied experienceAbstract”, Psychonomic Bulletin & Review, 2023.
CBMM Funded
T. Galanti, Xu, M., Galanti, L., and Poggio, T., “Norm-based Generalization Bounds for Sparse Neural Networks”, in NeurIPS 2023, New Orleans, 2023.PDF icon NeurIPS-2023-norm-based-generalization-bounds-for-sparse-neural-networks-Paper-Conference.pdf (577.69 KB)
CBMM Funded
G. Gaziv, Lee, M. J., and DiCarlo, J. J., “Strong and Precise Modulation of Human Percepts via Robustified ANNs”, in NeurIPS 2023, 2023.
CBMM Funded
G. Meanti*, Chatalic, A., Kostic, V. R., Novelli, P., Pontil, M., and Rosasco, L., “Estimating Koopman operators with sketching to provably learn large scale dynamical systems”, in 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.
CBMM Funded
M. Rando, Molinari, C., Villa, S., and Rosasco, L., “An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization”, in 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.
CBMM Funded
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

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