All Publications

2023

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
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
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

2022

J. Bill, Gershman, S. J., and Drugowitsch, J., “Visual motion perception as online hierarchical inference”, Nature Communications, vol. 13, no. 1, 2022.
CBMM Funded
T. Pouncy and Gershman, S. J., “Inductive biases in theory-based reinforcement learning”, Cognitive Psychology, vol. 138, p. 101509, 2022.
CBMM Funded
M. Letizia, Losapio, G., Rando, M., Grosso, G., Wulzer, A., Pierini, M., Zanetti, M., and Rosasco, L., “Learning new physics efficiently with nonparametric methodsAbstract”, The European Physical Journal C, vol. 82, no. 10, 2022.
CBMM Related
S. Liu, Pepe, B., Kumar, M. Ganesh, Ullman, T. D., Tenenbaum, J. B., and Spelke, E. S., “Dangerous Ground: One-Year-Old Infants are Sensitive to Peril in Other Agents’ Action PlansAbstract”, Open Mind, vol. 6, pp. 211 - 231, 2022.
CBMM Funded
F. Montagna, Noceti, N., Rosasco, L., Zhang, K., and Locatello, F., “Scalable Causal Discovery with Score Matching”, NeurIPS 2022. 2022.
CBMM Related
S. Dae Houlihan, Ong, D., Cusimano, M., and Saxe, R., “Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind”, Proceedings of the Annual Conference of the Cognitive Science Society, vol. 44. Toronto, CA, pp. 854-861, 2022.PDF icon Houlihan 2022 Proceedings of the 44th Annual Conference of the Cognitive Science Society.pdf (687.98 KB)
CBMM Funded
M. A. Sherman, Yaari, A. U., Priebe, O., Dietlein, F., Loh, P. - R., and Berger, B., “Genome-wide mapping of somatic mutation rates uncovers drivers of cancerAbstract”, Nature Biotechnology, vol. 40, no. 11, pp. 1634 - 1643, 2022.
CBMM Related
R. Tejwani, Kuo, Y. - L., Shu, T., Stankovits, B., Gutfreund, D., Tenenbaum, J. B., Katz, B., and Barbu, A., “Incorporating Rich Social Interactions Into MDPs”, in 2022 IEEE International Conference on Robotics and Automation (ICRA)2022 International Conference on Robotics and Automation (ICRA), Philadelphia, PA, USA, 2022.
CBMM Funded
N. Zaslavsky, Garvin, K., Kemp, C., Tishby, N., and Regier, T., “The evolution of color naming reflects pressure for efficiency: Evidence from the recent pastAbstract”, Journal of Language Evolution, 2022.
CBMM Related
CBMM Memo No.
133
R. Tejwani, Kuo, Y. - L., Shu, T., Stankovits, B., Gutfreund, D., Tenenbaum, J. B., Katz, B., and Barbu, A., “Incorporating Rich Social Interactions Into MDPs”. 2022.PDF icon CBMM-Memo-133.pdf (1.68 MB)
CBMM Funded
CBMM Memo No.
132
Y. - L. Kuo, Huang, X., Barbu, A., McGill, S. G., Katz, B., Leonard, J. J., and Rosman, G., “Trajectory Prediction with Linguistic Representations”. 2022.PDF icon CBMM-Memo-132.pdf (1.15 MB)
CBMM Funded
E. Cheng, Kuo, Y. - L., Correa, J., Katz, B., Cases, I., and Barbu, A., “Quantifying the Emergence of Symbolic Communication”, CogSci, 2022.
CBMM Related
E. Cheng, Kuo, Y. - L., Cases, I., Katz, B., and Barbu, A., “Spontaneous sign emergence in humans and machines through an embodied communication game”, in JCoLE Workshop, 2022.
CBMM Related
Y. - L. Kuo, Huang, X., Barbu, A., McGill, S. G., Katz, B., Leonard, J. J., and Rosman, G., “Trajectory Prediction with Linguistic Representations”, in 2022 IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, PA, USA, 2022.
CBMM Funded
A. Yaari, DeWitt, J., Hu, H., Stankovits, B., Felshin, S., Berzak, Y., Aparicio, H., Katz, B., Cases, I., and Barbu, A., “The Aligned Multimodal Movie Treebank: An audio, video, dependency-parse treebank”, in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022.
CBMM Related

2021

C. Bongiorno, Zhou, Y., Kryven, M., Theurel, D., Rizzo, A., Santi, P., Tenenbaum, J. B., and Ratti, C., “Vector-based pedestrian navigation in cities”, Nature Computational Science, vol. 1, no. 10, pp. 678 - 685, 2021.PDF icon s43588-021-00130-y.pdf (1.96 MB)
CBMM Funded
A. Uri Yaari, Sherman, M., Priebe, O. Clarke, Loh, P. - R., Katz, B., Barbu, A., and Berger, B., “Multi-resolution modeling of a discrete stochastic process identifies causes of cancer”, in International Conference on Learning Representations, 2021.
CBMM Funded
I. Palmer, Rouditchenko, A., Barbu, A., Katz, B., and Glass, J., “Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset”, in Interspeech 2021, ISCA, 2021.
CBMM Funded
Y. - L. Kuo, Katz, B., and Barbu, A., “Compositional RL Agents That Follow Language Commands in Temporal Logic”, Frontiers in Robotics and AI, vol. 8, 2021.PDF icon frobt-08-689550.pdf (1.57 MB)
CBMM Funded

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