All Publications

2020

H. Mhaskar and Poggio, T., Function approximation by deep networks, Communications on Pure & Applied Analysis, vol. 19, no. 8, pp. 4085 - 4095, 2020.PDF icon 1534-0392_2020_8_4085.pdf (514.57 KB)
CBMM Funded
CBMM Funded
CBMM Funded
Y. - L. Kuo, Katz, B., and Barbu, A., Deep compositional robotic planners that follow natural language commands , in International Conference on Robotics and Automation (ICRA), Palais des Congrès de Paris, Paris, France, 2020.
CBMM Funded
G. Ben-Yosef, Kreiman, G., and Ullman, S., What can human minimal videos tell us about dynamic recognition models?, in International Conference on Learning Representations (ICLR 2020), Virtual Conference, 2020.PDF icon Authors' final version (516.09 KB)
CBMM Funded
I. Dasgupta, Schulz, E., Tenenbaum, J. B., and Gershman, S. J., A theory of learning to infer., Psychological Review, vol. 127, no. 3, pp. 412 - 441, 2020.
CBMM Funded
T. Eisape, Levy, R., Tenenbaum, J. B., and Zaslavsky, N., Toward human-like object naming in artificial neural systems , in International Conference on Learning Representations (ICLR 2020), Bridging AI and Cognitive Science workshop, Virtual conference (due to Covid-19), 2020.
CBMM Funded
CBMM Related
CBMM Funded
N. Zaslavsky, Hu, J., and Levy, R., Emergence of Pragmatic Reasoning From Least-Effort Optimization , in 13th International Conference on the Evolution of Language (EvoLang) , The conference was canceled due to Covid-19, 2020.
CBMM Funded

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