CBMM Memo Series: Recent submissions

Now showing items 82-84 of 149

    • Do Deep Neural Networks Suffer from Crowding? 

      Volokitin, Anna; Roig, Gemma; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), arXiv, 2017-06-26)
      Crowding is a visual effect suffered by humans, in which an object that can be recognized in isolation can no longer be recognized when other objects, called flankers, are placed close to it. In this work, we study the ...

    • Symmetry Regularization 

      Anselmi, Fabio; Evangelopoulos, Georgios; Rosasco, Lorenzo; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), 2017-05-26)
      The properties of a representation, such as smoothness, adaptability, generality, equivari- ance/invariance, depend on restrictions imposed during learning. In this paper, we propose using data symmetries, in the sense of ...

    • On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations 

      Cheney, Nicholas; Schrimpf, Martin; Kreiman, Gabriel (Center for Brains, Minds and Machines (CBMM), arXiv, 2017-04-03)
      Deep convolutional neural networks are generally regarded as robust function approximators. So far, this intuition is based on perturbations to external stimuli such as the images to be classified. Here we explore the ...