5 papers
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…
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…
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…
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…
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…