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

  • Samuel May (Boston University)

  • Indara Suarez (Boston University)

Presentations and Publications
Current Status

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