5 papers
Calibrating Ambiguity Set via Diagnostic Transport for Distributionally Robust Optimization
Wenbin Zhou, Elizabeth Cucuzzella, Shixiang Zhu
Distributionally robust optimization (DRO) protects decisions against distributional uncertainty by optimizing over an ambiguity set, but poorly aligned set geometry can require la…
Trustworthy Predictive Distributions for Tail Events with Semiparametric Diagnostic Transport Maps
Elizabeth Cucuzzella, Rafael Izbicki, Ann B. Lee
Machine learning forecast systems are moving beyond point predictions to full predictive distributions for future outcomes y conditional on complex inputs x. However, these distrib…
Multi-Resolution Analysis of the Convective Structure of Tropical Cyclones for Short-Term Intensity Guidance
Elizabeth Cucuzzella, Tria McNeely, Kimberly Wood +1
Accurate tropical cyclone (TC) short-term intensity forecasting with a 24-hour lead time is essential for disaster mitigation in the Atlantic TC basin. Since most TCs evolve far fr…
Parametric Sensitivities of a Wind-driven Baroclinic Ocean Using Neural Surrogates
Yixuan Sun, Elizabeth Cucuzzella, Steven Brus +6
Numerical models of the ocean and ice sheets are crucial for understanding and simulating the impact of greenhouse gases on the global climate. Oceanic processes affect phenomena s…
Surrogate Neural Networks to Estimate Parametric Sensitivity of Ocean Models
Yixuan Sun, Elizabeth Cucuzzella, Steven Brus +5
Modeling is crucial to understanding the effect of greenhouse gases, warming, and ice sheet melting on the ocean. At the same time, ocean processes affect phenomena such as hurrica…