9 papers
Conformal Prediction Sets for Instance Segmentation
Kerri Lu, Dan M. Kluger, Stephen Bates +1
Current instance segmentation models achieve high performance on average predictions, but lack principled uncertainty quantification: their outputs are not calibrated, and there is…
Observation-driven correction of numerical weather prediction for marine winds
Matteo Peduto, Qidong Yang, Jonathan Giezendanner +2
Accurate marine wind forecasts are essential for safe navigation, ship routing, and energy operations, yet they remain challenging because observations over the ocean are sparse, h…
Invariant Features for Global Crop Type Classification
Xin-Yi Tong, Sherrie Wang
Accurate global crop type mapping supports agricultural monitoring and food security, yet remains limited by the scarcity of labeled data in many regions. A key challenge is enabli…
Partial recovery of meter-scale surface weather
Jonathan Giezendanner, Qidong Yang, Eric Schmitt +7
Near-surface atmospheric conditions can differ sharply over tens to hundreds of meters due to land cover and topography, yet this variability is absent from current weather analyse…
Conformal Prediction for Generative Models via Adaptive Cluster-Based Density Estimation
Qidong Yang, Qianyu Julie Zhu, Jonathan Giezendanner +3
Conditional generative models map input variables to complex, high-dimensional distributions, enabling realistic sample generation in a diverse set of domains. A critical challenge…
Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling
Dan M. Kluger, Kerri Lu, Tijana Zrnic +2
Machine learning models are increasingly used to produce predictions that serve as input data in subsequent statistical analyses. For example, computer vision predictions of econom…