activity
20172022
most citedConformalized Quantile Regression

51 citations · 99 across the 6 of their papers we have counts for

collaborators

15 papers

cs.LG202214 cited

Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging

Anastasios N Angelopoulos, Amit P Kohli, Stephen Bates +5

Image-to-image regression is an important learning task, used frequently in biological imaging. Current algorithms, however, do not generally offer statistical guarantees that prot…

stat.ME20217 cited

Searching for consistent associations with a multi-environment knockoff filter

Shuangning Li, Matteo Sesia, Yaniv Romano +2

This paper develops a method based on model-X knockoffs to find conditional associations that are consistent across diverse environments, controlling the false discovery rate. The…

cs.LG20216 cited

Improving Conditional Coverage via Orthogonal Quantile Regression

Shai Feldman, Stephen Bates, Yaniv Romano

We develop a method to generate prediction intervals that have a user-specified coverage level across all regions of feature-space, a property called conditional coverage. A typica…

stat.ME2021

Conformal Prediction using Conditional Histograms

Matteo Sesia, Yaniv Romano

This paper develops a conformal method to compute prediction intervals for non-parametric regression that can automatically adapt to skewed data. Leveraging black-box machine learn…

stat.ML202021 cited

Achieving Equalized Odds by Resampling Sensitive Attributes

Yaniv Romano, Stephen Bates, Emmanuel J. Candès

We present a flexible framework for learning predictive models that approximately satisfy the equalized odds notion of fairness. This is achieved by introducing a general discrepan…

stat.ME2020

Classification with Valid and Adaptive Coverage

Yaniv Romano, Matteo Sesia, Emmanuel J. Candès

Conformal inference, cross-validation+, and the jackknife+ are hold-out methods that can be combined with virtually any machine learning algorithm to construct prediction sets with…