Publications

(2024). Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference. Proceedings of the Forty-First International Conference on Machine Learning (ICML 2024), PMLR 235, 2024.

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(2022). Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems. Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), PMLR 206:2960-2974, 2023. (Finalist at the ASA SPES and Q&P Student Paper Competition).

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(2022). Detecting Distributional Differences in Labeled Sequence Data with Application to Tropical Cyclone Satellite Imagery. Annals of Applied Statistics 17(2):1260-1284, June 2023. (Selected for The Best of AOAS invited paper session at JSM 2023).

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(2021). Diagnostics for Conditional Density Models and Bayesian Inference Algorithms. Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021). PMLR 161:1830-1840, 2021.

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(2020). Wildfire Smoke and Air Quality: How Machine Learning Can Guide Forest Management. Tackling Climate Change with Machine Learning workshop at NeurIPS 2020 (Spotlight talk).

Preprint Slides Video

(2020). Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting. Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML 2020), PMLR 119:2323-2334, 2020.

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(2019). Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS 2020), PMLR 108:3349-3361, 2020.

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(2019). Global and Local Two-Sample Tests via Regression. Electronic Journal of Statistics, 13(2): 5253-5305, 2019.

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(2017). Local Two-Sample Testing: A New Tool for Analysing High-Dimensional Astronomical Data. Monthly Notices of the Royal Astronomical Society (MNRAS), 471(3): 3273-3282, 2017.

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(2015). Nonparametric Conditional Density Estimation in a High-Dimensional Regression Setting.. Journal of Computational and Graphical Statistics, 25(4): 1297-1316, 2016.

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