IRIS-HEP Fellow: Hector Castro Noguez



Fellowship dates: Jun – Aug, 2020

Home Institution: Boston University


Project: Domain Adaptation via Histogram Loss Component

While gradient reversal layers are shown to be successful, it is possible to take a more direct approach to improving the agreement between data and simulation. Rather than discourage the DNN from learning features which allow it to distinguish between examples from the source and target domain (as done for the gradient reversal layer), we propose to explicitly reward the DNN for minimizing differences between distributions in the source and target domains.

More information: My project proposal

Mentors:
  • Samuel May (Boston University)

  • Indara Suarez (Boston University)

Presentations
Current Status


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