publications

2025

1. Conformal Prediction With Conditional Guarantees

   Isaac Gibbs, John J Cherian, and Emmanuel J Candès

   Accepted at Journal of the Royal Statistical Society: Series B, 2025

   Bib PDF Code

   @article{gibbs2023conformal,
     title = {Conformal Prediction With Conditional Guarantees},
     author = {Gibbs, Isaac and Cherian, John J and Cand{\`e}s, Emmanuel J},
     journal = {Accepted at Journal of the Royal Statistical Society: Series B},
     year = {2025},
     url = {https://arxiv.org/abs/2305.12616},
     abs = {https://arxiv.org/abs/2305.12616},
     month = {}
   }

2024

1. Large language model validity via enhanced conformal prediction methods

   John J Cherian, Isaac Gibbs, and Emmanuel J Candès

   In Advances in Neural Information Processing Systems, 2024

   Bib PDF Code

   @inproceedings{cherian2024llm,
     author = {Cherian, John J and Gibbs, Isaac and Cand{\`e}s, Emmanuel J},
     booktitle = {Advances in Neural Information Processing Systems},
     editor = {Globerson, A. and Mackey, L. and Fan, A. and Zhang, C. and Belgrave, D. and Tomczak, J. and Pacquet, U.},
     publisher = {Curran Associates, Inc.},
     title = {Large language model validity via enhanced conformal prediction methods},
     url = {https://arxiv.org/abs/2406.09714},
     abs = {https://arxiv.org/abs/2406.09714},
     volume = {37},
     year = {2024},
     month = {}
   }

2. Statistical Inference for Fairness Auditing

   John J Cherian, and Emmanuel J Candès

   Journal of Machine Learning Research, 2024

   Bib PDF Code

   @article{cherian2024statistical,
     title = {Statistical Inference for Fairness Auditing},
     author = {Cherian, John J and Cand{\`e}s, Emmanuel J},
     journal = {Journal of Machine Learning Research},
     year = {2024},
     volume = {25},
     number = {149},
     pages = {1--49},
     url = {https://www.jmlr.org/papers/v25/23-0739.html},
     abs = {https://www.jmlr.org/papers/v25/23-0739.html},
     month = {}
   }

3. Election modeling in 2024: a conformal inference approach

   John J Cherian, Lenny Bronner, and Emmanuel J Candès

   Oct 2024

   Bib HTML Code Poster

   @techreport{cherianbronner2024post,
     author = {Cherian, John J and Bronner, Lenny and Cand{\`e}s, Emmanuel J},
     institution = {The Washington Post},
     title = {Election modeling in 2024: a conformal inference approach},
     year = {2024},
     month = oct,
   }

2020

1. Efficient hyperparameter optimization by way of PAC-Bayes bound minimization

   John J Cherian, Andrew G Taube, Robert T McGibbon, and 6 more authors

   arXiv preprint arXiv:2008.06431, 2020

   Bib PDF Code

   @article{cherian2020efficient,
     title = {Efficient hyperparameter optimization by way of PAC-Bayes bound minimization},
     author = {Cherian, John J and Taube, Andrew G and McGibbon, Robert T and Angelikopoulos, Panagiotis and Blanc, Guy and Snarski, Michael and Richman, Daniel D and Klepeis, John L and Shaw, David E},
     journal = {arXiv preprint arXiv:2008.06431},
     year = {2020},
     url = {https://arxiv.org/abs/2008.06431},
     abs = {https://arxiv.org/abs/2008.06431},
     month = {}
   }

2. How The Washington Post estimates outstanding votes for the 2020 presidential election

   John J Cherian, and Lenny Bronner

   Oct 2020

   Bib PDF

   @techreport{cherianbronner2020post,
     author = {Cherian, John J and Bronner, Lenny},
     institution = {The Washington Post},
     title = {How {The Washington Post} estimates outstanding votes for the 2020 presidential election},
     year = {2020},
     month = oct
   }

3. An update to The Washington Post Election Night Model

   John J Cherian, and Lenny Bronner

   Dec 2020

   Bib PDF

   @techreport{cherianbroner2020postv2,
     author = {Cherian, John J and Bronner, Lenny},
     institution = {The Washington Post},
     title = {An update to {The Washington Post Election Night Model}},
     year = {2020},
     month = dec,
   }