All Publications

2018

T. Poggio and Liao, Q., Theory I: Deep networks and the curse of dimensionality, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 66, no. 6, 2018.PDF icon 02_761-774_00966_Bpast.No_.66-6_28.12.18_K1.pdf (1.18 MB)
CBMM Funded
T. Poggio and Liao, Q., Theory II: Deep learning and optimization, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 66, no. 6, 2018.PDF icon 03_775-788_00920_Bpast.No_.66-6_31.12.18_K2.pdf (5.43 MB)
CBMM Funded
J. Sliwa, Marvel, S. R., Ianni, G. A., and Freiwald, W. A., Comparing human and monkey neural circuits for processing social scenes, Société Francophone de Primatologie (SFDP) Annual Meeting, Paris, France. 2018.
CBMM Funded
J. Sliwa, Marvel, S. R., Ianni, G. A., and Freiwald, W. A., Comparing human and monkey neural circuits for processing social scenes, Cognitive Neuroscience Society Annual Meeting (CNS), Boston, MA. 2018.
CBMM Funded
J. Traer and McDermott, J. H., Human recognition of environmental sounds is not always robust to reverberation, Annual Meeting of the Acoustical Society, vol. 143, no. 3. 2018.
CBMM Related
J. Wang, Zhang, Z., Xie, C., Zhou, Y., Premachandran, V., Zhu, J., Xie, L., and Yuille, A., Visual Concepts and Compositional Voting, Annals of Mathematical Sciences and Applications (AMSA), vol. 3, no. 1, pp. 151–188, 2018.
CBMM Funded

2017

CBMM Funded
CBMM Related
J. Jara-Ettinger, Floyd, S., Tenenbaum, J. B., and Schulz, L., Children understand that agents maximize expected utilities., Journal of Experimental Psychology: General, vol. 146, no. 11, pp. 1574 - 1585, 2017.PDF icon ExpectedUtilities_Final.pdf (950.09 KB)
CBMM Related
CBMM Related
CBMM Related
CBMM Related
CBMM Funded
M. Janner, Wu, J., Kulkarni, T., Yildirim, I., and Tenenbaum, J. B., Self-supervised intrinsic image decomposition., in Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, CA, 2017.PDF icon intrinsicImg_nips_2017.pdf (5.87 MB)
CBMM Funded
A. Tacchetti, Isik, L., and Poggio, T., Invariant recognition drives neural representations of action sequences, PLOS Computational Biology, vol. 13, no. 12, p. e1005859, 2017.PDF icon journal.pcbi_.1005859.pdf (9.24 MB)
CBMM Funded
J. Wu, Lu, E., Kohli, P., Freeman, W. T., and Tenenbaum, J. B., Learning to See Physics via Visual De-animation, Advances in Neural Information Processing Systems 30. pp. 152–163, 2017.PDF icon Learning to See Physics via Visual De-animation (1.11 MB)
CBMM Funded

Pages