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Prediction Intervals

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A prediction interval is an estimate of an interval in which a future observation will fall, with a certain probability, given what has already been observed. Prediction intervals are often used in regression analysis.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/msesia/chr

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Conformal Prediction using Conditional Histograms

https://github.com/msesia/cqr-comparison

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A comparison of some conformal quantile regression methods

https://github.com/mufangying/informativeness-of-wcp

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Informativeness of Weighted Conformal Prediction

https://github.com/mzaffran/adaptiveconformalpredictionstimeseries

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Adaptive Conformal Predictions for Time Series

https://github.com/mzaffran/conformalpredictionmissingvalues

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Conformal Prediction with Missing Values

https://github.com/ndiamant/spice

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Conformalized Deep Splines for Optimal and Efficient Prediction Sets

https://github.com/neitzal/adaptive-skip-intervals

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Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models

https://github.com/nicoloRHUL/NormalizingFlowsForConformalRegression

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Normalizing Flows for Conformal Regression

https://github.com/nicolorhul/ontraininglocalizedcp

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On training locally adaptive CP

https://github.com/nmdwolf/ValidPredictionIntervals

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Valid prediction intervals for regression problems

https://github.com/nmdwolf/heteroskedasticconformalregression

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Conditional validity of heteroskedastic conformal regression

https://github.com/olivrw/LP-robust-conformal

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Conformal Prediction under Levy-Prokhorov Distribution Shifts: Robustness to Local and Global Perturbations

https://github.com/paulkogni/SG-RCPS

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Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy

https://github.com/ppernot/2024_picp

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On the good reliability of an interval-based metric to validate prediction uncertainty for machine learning regression tasks

https://github.com/precise-ai4oph/va_pred_pac

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Fundus Image-based Visual Acuity Assessment with PAC-Guarantees

https://github.com/predict-idlab/cct-cmc

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Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects

https://github.com/predict-idlab/cmc-learner

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Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects

https://github.com/predict-idlab/dose-response-conformal-prediction

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Conformal Prediction for Dose-Response Models with Continuous Treatments

https://github.com/quilograma/aenbmimocqr

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A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecasting

https://github.com/ran-xie/boosted-conformal

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Boosted Conformal Prediction Intervals

https://github.com/richard759/fetsmcs

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fETSmcs: Feature-based ETS model component selection

https://github.com/rrross/uacqr

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Integrating Uncertainty Awareness into Conformalized Quantile Regression

https://github.com/ryantibs/conformal

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Distribution-Free Predictive Inference For Regression

https://github.com/saattrupdan/doubt

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Monitoring Model Deterioration with Explainable Uncertainty Estimation via Non-parametric Bootstrap

https://github.com/samuelstanton/conformal-bayesopt

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Bayesian Optimization with Conformal Prediction Sets

https://github.com/seedatnabeel/sscp

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Improving Adaptive Conformal Prediction Using Self-Supervised Learning

https://github.com/ssokota/spie

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Simultaneous Prediction Intervals for Patient-Specific Survival Curves

https://github.com/statmixedml/dgbm

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Distributional Gradient Boosting Machines

https://github.com/suntiansheng/llm-cpi-prediction-and-inference

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LLM-Powered CPI Prediction Inference with Online Text Time Series

https://github.com/tarik/pi-snm-qde

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Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles

https://github.com/tpouplin/rqr

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Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise

https://github.com/usarawgi911/Uncertainty-aware-boosting

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Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings

https://github.com/vanderschaarlab/sscp

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Improving Adaptive Conformal Prediction Using Self-Supervised Learning

https://github.com/vincentblot28/conformalized_gp

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Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees

https://github.com/vladislav-morozov/noisy-extreme

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Inference on Extreme Quantiles of Unobserved Individual Heterogeneity

https://github.com/yifei-liu-stat/pass

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Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty Quantification

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