Conformal Prediction

64 papers with code • 0 benchmarks • 0 datasets

This task has no description! Would you like to contribute one?

Most implemented papers

Conformalized Quantile Regression

yromano/cqr NeurIPS 2019

Conformal prediction is a technique for constructing prediction intervals that attain valid coverage in finite samples, without making distributional assumptions.

An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls

kwuthrich/scinference 25 Dec 2017

We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation.

Uncertainty Sets for Image Classifiers using Conformal Prediction

aangelopoulos/conformal-classification ICLR 2021

Convolutional image classifiers can achieve high predictive accuracy, but quantifying their uncertainty remains an unresolved challenge, hindering their deployment in consequential settings.

Conformal prediction interval for dynamic time-series

hamrel-cxu/EnbPI 18 Oct 2020

We develop a method to construct distribution-free prediction intervals for dynamic time-series, called \Verb|EnbPI| that wraps around any bootstrap ensemble estimator to construct sequential prediction intervals.

Conformalized Survival Analysis

zhimeir/cfsurv_paper 17 Mar 2021

Existing survival analysis techniques heavily rely on strong modelling assumptions and are, therefore, prone to model misspecification errors.

Adaptive Conformal Predictions for Time Series

mzaffran/adaptiveconformalpredictionstimeseries 15 Feb 2022

While recent works tackled this issue, we argue that Adaptive Conformal Inference (ACI, Gibbs and Cand{\`e}s, 2021), developed for distribution-shift time series, is a good procedure for time series with general dependency.

Conformal prediction set for time-series

hamrel-cxu/ensemble-regularized-adaptive-prediction-set-eraps 15 Jun 2022

When building either prediction intervals for regression (with real-valued response) or prediction sets for classification (with categorical responses), uncertainty quantification is essential to studying complex machine learning methods.

Model-Robust Counterfactual Prediction Method

dzachariah/counterfactual 19 May 2017

We develop a novel method for counterfactual analysis based on observational data using prediction intervals for units under different exposures.

libconform v0.1.0: a Python library for conformal prediction

jofas/conform 3 Jul 2019

This paper introduces libconform v0. 1. 0, a Python library for the conformal prediction framework, licensed under the MIT-license.