1 citations · 2 across the 9 of their papers we have counts for
10 papers
Prediction-powered inference for time series across space
Shahzar Rizvi, David Burt, Vishwak Srinivasan +3
The following motif is common in spatiotemporal settings: we have a sequence of covariate and label pairs observed for a relatively short, recent time period. We have access to unl…
Wrong Model, Right Uncertainty: Spatial Associations for Discrete Data with Misspecification
David R. Burt, Renato Berlinghieri, Tamara Broderick
Scientists are often interested in estimating an association between a covariate and a binary- or count-valued response. For instance, public health officials are interested in how…
Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings
Jenny Y. Huang, Yunyi Shen, Dennis Wei +1
We propose a method for evaluating the robustness of widely used LLM ranking systems -- variants of a Bradley--Terry model -- to dropping a worst-case very small fraction of prefer…
Oh SnapMMD! Forecasting Stochastic Dynamics Beyond the Schrödinger Bridge's End
Renato Berlinghieri, Yunyi Shen, Jialong Jiang +1
Scientists often want to make predictions beyond the observed time horizon of "snapshot" data following latent stochastic dynamics. For example, in time course single-cell mRNA pro…
Wild posteriors in the wild
Yunyi Shen, Tamara Broderick
Bayesian posterior approximation has become more accessible to practitioners than ever, thanks to modern black-box software. While these tools provide highly accurate approximation…
Smooth Sailing: Lipschitz-Driven Uncertainty Quantification for Spatial Association
David R. Burt, Renato Berlinghieri, Stephen Bates +1
Estimating associations between spatial covariates and responses - rather than merely predicting responses - is central to environmental science, epidemiology, and economics. For i…
Are Hourly PM2.5 Forecasts Sufficiently Accurate to Plan Your Day? Individual Decision Making in the Face of Increasing Wildfire Smoke
Renato Berlinghieri, David R. Burt, Paolo Giani +2
Wildfire frequency is increasing as the climate changes, and the resulting air pollution poses health risks. Just as people routinely use hourly weather forecasts to plan their day…
Approximations to worst-case data dropping: unmasking failure modes
Jenny Y. Huang, David R. Burt, Yunyi Shen +2
A data analyst might worry about generalization if dropping a very small fraction of data points from a study could change its substantive conclusions. Checking this non-robustness…
Multi-marginal Schrödinger Bridges with Iterative Reference Refinement
Yunyi Shen, Renato Berlinghieri, Tamara Broderick
Practitioners often aim to infer an unobserved population trajectory using sample snapshots at multiple time points. E.g., given single-cell sequencing data, scientists would like…
Consistent Validation for Predictive Methods in Spatial Settings
David R. Burt, Yunyi Shen, Tamara Broderick
Spatial prediction tasks are key to weather forecasting, studying air pollution impacts, and other scientific endeavors. Determining how much to trust predictions made by statistic…