Jake Fawkes

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Causal Inference, Machine Learning, Fairness

Hello! I am a DPhil student working under the supervision of Dino Sejdinovic and Robin Evans. My research centers on causal machine learning with a focus on causal inference for fairness. I am also more generally interested in domain generalisation, the theory of causal inference and kernel methods. If you have any questions please feel free to reach out to me at jake.fawkes@stats.ox.ac.uk.

Publications

2023

• S. Bouabid , J. Fawkes , D. Sejdinovic , Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge, arXiv preprint arXiv:2301.11214, 2023.
  

  @article{bouabid2023returning,
    title = {Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge},
    author = {Bouabid, Shahine and Fawkes, Jake and Sejdinovic, Dino},
    journal = {arXiv preprint arXiv:2301.11214},
    year = {2023}
  }
  

2022

• J. Fawkes , R. J. Evans , D. Sejdinovic , Selection, ignorability and challenges with causal fairness, in Conference on Causal Learning and Reasoning, 2022, 275–289.
  

  @inproceedings{fawkes22selection,
    title = {Selection, ignorability and challenges with causal fairness},
    author = {Fawkes, Jake and Evans, R. J. and Sejdinovic, Dino},
    booktitle = {Conference on Causal Learning and Reasoning},
    pages = {275--289},
    year = {2022},
    organization = {PMLR},
    archiveprefix = {arXiv},
    eprint = {2202.13774}
  }
  

• J. Fawkes , R. Evans , D. Sejdinovic , Selection, Ignorability and Challenges With Causal Fairness, arXiv preprint arXiv:2202.13774, 2022.
  

  @article{fawkes2022selection,
    title = {Selection, Ignorability and Challenges With Causal Fairness},
    author = {Fawkes, Jake and Evans, Robin and Sejdinovic, Dino},
    journal = {arXiv preprint arXiv:2202.13774},
    year = {2022}
  }