All Publications

2024

F. Montagna, Mastakouri, A. A., Eulig, E., Noceti, N., Rosasco, L., Janzing, D., Aragam, B., and Locatello, F., “Assumption violations in causal discovery and the robustness of score matching”, in 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2024.
CBMM Related
F. Ceola, Rosasco, L., Natale, L., and Ceola, F., “RESPRECT: Speeding-up Multi-Fingered Grasping With Residual Reinforcement LearningRESPRECT: Speeding-Up Multi-Fingered Grasping With Residual Reinforcement Learning_supp1-3363532.mp4”, IEEE Robotics and Automation Letters, vol. 9, no. 4, pp. 3045 - 3052, 2024.
CBMM Funded
S. J. Gershman, “What have we learned about artificial intelligence from studying the brain?”, Biological Cybernetics, vol. 118, no. 1-2, pp. 1 - 5, 2024.
CBMM Funded

2023

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
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
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
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
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
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
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
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
Y. Xiang, Vélez, N., and Gershman, S. J., “Collaborative decision making is grounded in representations of other people’s competence and effort.”, Journal of Experimental Psychology: General, vol. 152, no. 6, pp. 1565 - 1579, 2023.
CBMM Funded
S. J. Gershman and Ullman, T. D., “Causal implicatures from correlational statements”, PLOS ONE, vol. 18, no. 5, p. e0286067, 2023.
CBMM Funded
N. Vélez, Chen, A. M., Burke, T., Cushman, F. A., and Gershman, S. J., “Teachers recruit mentalizing regions to represent learners’ beliefs”, Proceedings of the National Academy of Sciences, vol. 120, no. 22, 2023.
CBMM Funded
D. Lagomarsino-Oneto, Meanti, G., Pagliana, N., Verri, A., Mazzino, A., Rosasco, L., and Seminara, A., “Physics informed machine learning for wind speed prediction”, Energy, vol. 268, p. 126628, 2023.
CBMM Funded
S. J. Gershman and Cikara, M., “Structure learning principles of stereotype change”, Psychonomic Bulletin & Review, vol. 30, no. 4, pp. 1273 - 1293, 2023.
CBMM Funded
V. Subramaniam, Conwell, C., Wang, C., Kreiman, G., Katz, B., Cases, I., and Barbu, A., “Using Multimodal DNNs to Study Vision-Language Integration in the Brain”, in ICLR 2023, 2023.
CBMM Funded
R. Tejwani, Kuo, Y. - L., Shu, T., Stankovits, B., Gutfreund, D., Tenenbaum, J. B., Katz, B., and Barbu, A., “Zero-shot linear combinations of grounded social interactions with Linear Social MDPs”, in Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.
CBMM Funded
C. Wang, Subramaniam, V., Yaari, A. Uri, Kreiman, G., Katz, B., Cases, I., and Barbu, A., “BrainBERT: Self-supervised representation learning for Intracranial Electrodes”, International Conference on Learning Representations. Kigali, Rwanda, Africa, 2023.PDF icon 985_brainbert_self_supervised_repr.pdf (9.71 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”, arXiv, 2023.
CBMM Related
S. Villa, Matet, S., Vũ, B. Công, and Rosasco, L., “Implicit regularization with strongly convex bias: Stability and acceleration”, Analysis and Applications, vol. 21, no. 01, pp. 165 - 191, 2023.
CBMM Related

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