6 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…
M-estimation under Two-Phase Multiwave Sampling with Applications to Prediction-Powered Inference
Dan M. Kluger, Stephen Bates
In two-phase multiwave sampling, inexpensive measurements are collected on a large sample and expensive, more informative measurements are adaptively obtained on subsets of units a…
Demystifying Prediction Powered Inference
Yilin Song, Dan M. Kluger, Harsh Parikh +1
Machine learning predictions are increasingly used to supplement incomplete or costly-to-measure outcomes in fields such as biomedical research, environmental science, and social s…
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…
Precrop Payoffs: Causal machine learning reveals large but variable yield benefits of crop rotation in major breadbaskets
Dan M. Kluger, Stefania Di Tommaso, David B. Lobell
Building sustainable food systems that are resilient to climate change will require improved agricultural management and policy. One common practice that is well-known to benefit c…
Regression coefficient estimation from remote sensing maps
Kerri Lu, Dan M. Kluger, Stephen Bates +1
Regressions are commonly used in environmental science and economics to identify causal or associative relationships between variables. In these settings, remote sensing-derived ma…