publications

2025

1. ICML

   Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets

   Charita Dellaporta^*, Patrick O’Hara^*, and Theodoros Damoulas

   To appear at the International Conference on Machine Learning, 2025

   arXiv Bib PDF

   @article{dellaporta2024decision,
     title = {Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets},
     author = {Dellaporta, Charita and O'Hara, Patrick and Damoulas, Theodoros},
     journal = {To appear at the International Conference on Machine Learning},
     year = {2025},
   }

2024

1. NeurIPS BDU

   Distributionally Robust Optimisation with Bayesian Ambiguity Sets

   Charita Dellaporta^*, Patrick O’Hara^*, and Theodoros Damoulas

   NeurIPS workshop in Bayesian Decision-making and Uncertainty, 2024

   arXiv Bib PDF

   @article{dellaporta2024distributionally,
     title = {Distributionally Robust Optimisation with Bayesian Ambiguity Sets},
     author = {Dellaporta, Charita and O'Hara, Patrick and Damoulas, Theodoros},
     journal = {NeurIPS workshop in Bayesian Decision-making and Uncertainty},
     year = {2024},
   }

2023

1. Under review

   Robust Bayesian Inference for Berkson and Classical Measurement Error Models

   Charita Dellaporta, and Theodoros Damoulas

   arXiv preprint arXiv:2306.01468, 2023

   arXiv Bib PDF

   @article{dellaporta2023robust,
     title = {Robust Bayesian Inference for Berkson and Classical Measurement Error Models},
     author = {Dellaporta, Charita and Damoulas, Theodoros},
     journal = {arXiv preprint arXiv:2306.01468},
     year = {2023},
   }

2022

1. AISTATS

   Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap

   Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, and François-Xavier Briol

   In International Conference on Artificial Intelligence and Statistics, 2022

   arXiv Bib PDF Code

   @inproceedings{dellaporta2022robust,
     title = {Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap},
     author = {Dellaporta, Charita and Knoblauch, Jeremias and Damoulas, Theodoros and Briol, Fran{\c{c}}ois-Xavier},
     booktitle = {International Conference on Artificial Intelligence and Statistics},
     pages = {943--970},
     year = {2022},
     organization = {PMLR},
   }