Now showing items 1-3 of 110

    • An Exit Strategy from the Covid-19 Lockdown based on Risk-sensitive Resource Allocation 

      Shalev-Shwartz, Shai; Shashua, Amnon (Center for Brains, Minds and Machines (CBMM), 2020-04-15)
      We propose an exit strategy from the COVID-19 lockdown, which is based on a risk-sensitive levels of social distancing. At the heart of our approach is the realization that the most effective, yet limited in number, resources ...
    • Do Neural Networks for Segmentation Understand Insideness? 

      Villalobos, Kimberly; Štih, Vilim; Ahmadinejad, Amineh; Sundaram, Shobhita; Dozier, Jamell; e.a. (Center for Brains, Minds and Machines (CBMM), 2020-04-04)
      The insideness problem is an image segmentation modality that consists of determining which pixels are inside and outside a region. Deep Neural Networks (DNNs) excel in segmentation benchmarks, but it is unclear that they ...
    • Can we Contain Covid-19 without Locking-down the Economy? 

      Shalev-Shwartz, Shai; Shashua, Amnon (Center for Brains, Minds and Machines (CBMM), 2020-03-26)
      We present an analysis of a risk-based selective quarantine model where the population is divided into low and high-risk groups. The high-risk group is quarantined until the low-risk group achieves herd-immunity. We tackle ...