Publications

Conditional Outcome Equivalence: A Quantile Alternative to CATE

Published in In the proceedings of Advances in Neural Information Processing Systems, 2024

This paper presents an alternative to the CATE called the conditional quantile comparator which rpovide a more complete characterisation of the treatment effect while maintaining the CATE’s nice estimation properties.

Recommended citation: Josh Givens, Henry Reeve, Song Liu, Katarzyna Reluga, "Conditional Outcome Equivalence: A Quantile Alternative to CATE." In the proceedings of Advances in Neural Information Processing Systems, 2024. https://arxiv.org/abs/2410.12454

Density Ratio Estimation and Neyman Pearson Classification with Missing Data

Published in In the proceedings of Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, 2023

This paper adapts Density Ratio Estimation techniques making them robust to missing not at random missing data before applying this to the field of Neyman Pearson classification.

Recommended citation: Josh Givens, Song Liu, Henry Reeve, "Density Ratio Estimation and Neyman Pearson Classification with Missing Data." In the proceedings of Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, 2023. https://proceedings.mlr.press/v206/givens23a.html