HAPNEST: an efficient tool for generating large-scale genetics datasets from limited training data

Sophie Wharrie, Zhiyu Yang, Vishnu Raj, Remo Monti, Rahul Gupta, Ying Ying Wang, Alicia R. Martin, Luke J O'Connor, Samuel Kaski, Pekka Marttinen, Pier Francesco Palamara, Christoph Lippert, Andrea Ganna

Research output: Contribution to conferenceAbstractpeer-review

Original languageEnglish
Publication statusPublished - 2022
EventNeurIPS Workshop on Synthetic Data for Empowering ML Research -
Duration: 2 Dec 20222 Dec 2022

Conference

ConferenceNeurIPS Workshop on Synthetic Data for Empowering ML Research
Period2/12/222/12/22

Keywords

  • synthetic data
  • ML for healthcare
  • computational genetics, approximate Bayesian computation

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