All Publications

2021

C. Ross, Katz, B., and Barbu, A., Measuring Social Biases in Grounded Vision and Language Embeddings, NAACL (Annual Conference of the North American Chapter of the Association for Computational Linguistics). 2021.
CBMM Funded

2020

T. Poggio, Banburski, A., and Liao, Q., Theoretical issues in deep networks, Proceedings of the National Academy of Sciences, p. 201907369, 2020.PDF icon PNASlast.pdf (915.3 KB)
CBMM Funded
S. Levine, Kleiman-Weiner, M., Schulz, L., Tenenbaum, J. B., and Cushman, F. A., The logic of universalization guides moral judgment, Proceedings of the National Academy of Sciences (PNAS), p. 202014505, 2020.
CBMM Funded
T. D. Ullman and Tenenbaum, J. B., Bayesian Models of Conceptual Development: Learning as Building Models of the World, Annual Review of Developmental Psychology, vol. 2, no. 1, pp. 533 - 558, 2020.
CBMM Funded
CBMM Funded
W. A. Freiwald, Gross means Great, Progress in Neurobiology, vol. 195, p. 101924, 2020.
CBMM Related
W. A. Freiwald, Social interaction networks in the primate brain, Current Opinion in Neurobiology, vol. 65, pp. 49 - 58, 2020.
CBMM Funded
E. Malkin, Deza, A., and Poggio, T., CUDA-Optimized real-time rendering of a Foveated Visual System, in Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020, 2020.PDF icon Foveated_Drone_SVRHM_2020.pdf (13.44 MB)PDF icon v1 (12/15/2020) (14.7 MB)
CBMM Funded
M. J. McPherson and McDermott, J. H., Time-dependent discrimination advantages for harmonic sounds suggest efficient coding for memory, Proceedings of the National Academy of Sciences, vol. 117, no. 50, pp. 32169 - 32180, 2020.
CBMM Related
CBMM Funded
M. Nye, Solar-Lezama, A., Tenenbaum, J. B., and Lake, B. M., Learning Compositional Rules via Neural Program Synthesis, in Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020), 2020.PDF icon 2003.05562.pdf (2.51 MB)
CBMM Funded
L. Tian, Ellis, K., Kryven, M., and Tenenbaum, J. B., Learning abstract structure for drawing by efficient motor program induction, in Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020), 2020.
CBMM Funded
S. - M. Udrescu, Tan, A., Feng, J., Neto, O., Wu, T., and Tegmark, M., AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity, in Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020), 2020.PDF icon 2006.10782.pdf (2.62 MB)
CBMM Funded
CBMM Funded
CBMM Funded
CBMM Memo No.
113
A. Banburski, Gandhi, A., Alford, S., Dandekar, S., Chin, P., and Poggio, T., Dreaming with ARC, Learning Meets Combinatorial Algorithms workshop at NeurIPS 2020. 2020.PDF icon CBMM Memo 113.pdf (1019.64 KB)
CBMM Funded

Pages