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Center for Brains, Minds & Machines

Research and Teaching Output of the MIT Community

Center for Brains, Minds & Machines

 

The Center for Brains, Minds and Machines (CBMM) is a National Science Foundation funded Science and Technology Center on the interdisciplinary study of intelligence. This effort is a multi-institutional collaboration headquartered at the McGovern Institute for Brain Research at MIT, with Harvard University as a managing partner. Visit the CBMM website for more information.

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Recent Submissions

  • Shen, Wei; Guo, Yilu; Wang, Yan; Zhao, Kai; Wang, Bo; Yuille, Alan L. (Center for Brains, Minds and Machines (CBMM), 2018-06-01)
    Age estimation from facial images is typically cast as a nonlinear regression problem. The main challenge of this problem is the facial feature space w.r.t. ages is inhomogeneous, due to the large variation in facial ...
  • Shen, Wei; Wang, Bin; Jiang, Yuan; Wang, Yan; Yuille, Alan L. (Center for Brains, Minds and Machines (CBMM), 2017-10-01)
    In the field of connectomics, neuroscientists seek to identify cortical connectivity comprehensively. Neuronal boundary detection from the Electron Microscopy (EM) images is often done to assist the automatic reconstruction ...
  • Zhang, Chiyuan; Liao, Qianli; Rakhlin, Alexander; Miranda, Brando; Golowich, Noah; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), 2017-12-27)
    In Theory IIb we characterize with a mix of theory and experiments the optimization of deep convolutional networks by Stochastic Gradient Descent. The main new result in this paper is theoretical and experimental evidence ...
  • Wang, Yu-Siang; Liu, Chenxi; Zeng, Xiaohui; Yuille, Alan L. (Center for Brains, Minds and Machines (CBMM), 2018-05-10)
    In this paper, we study the problem of parsing structured knowledge graphs from textual descrip- tions. In particular, we consider the scene graph representation that considers objects together with their attributes and ...
  • Liu, Chenxi; Lin, Zhe; Shen, Xiaohui; Yang, Jimei; Lu, Xin; Yuille, Alan L. (Center for Brains, Minds and Machines (CBMM), 2018-05-10)
    In this paper we are interested in the problem of image segmentation given natural language descriptions, i.e. referring expressions. Existing works tackle this problem by first modeling images and sentences independently ...
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