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Conformal Prediction
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Conformal Prediction is a machine learning framework that provides valid measures of confidence for individual predictions. It offers a principled approach to quantify uncertainty in predictions without assuming any specific distribution for the data. This section features papers that explore various aspects of conformal prediction, including theoretical advancements, algorithmic developments, and applications across different domains.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/larsvanderlaan/selfcalibratingconformal
공식 코드https://github.com/layer6ai-labs/conformal-prediction-fairness
공식 코드https://github.com/layer6ai-labs/hitl-conformal-prediction
공식 코드https://github.com/lclarte/conformalamp.jl
공식 코드Building Conformal Prediction Intervals with Approximate Message Passing
https://github.com/lee-group-cmu/cal-pit
공식 코드https://github.com/lefterisvl83/cdc25
공식 코드https://github.com/lei-ding07/conformal_quantile_fairness
공식 코드https://github.com/ltpritamanand/tube_loss
공식 코드Tube Loss: A Novel Approach for Prediction Interval Estimation and probabilistic forecasting
https://github.com/luo-lorry/CIA
공식 코드Conformalized Interval Arithmetic with Symmetric Calibration
https://github.com/luo-lorry/conformal-load-forecasting
공식 코드Conformal Load Prediction with Transductive Graph Autoencoders
https://github.com/luo-lorry/cti
공식 코드https://github.com/m-schroder/continuouscausalcp
공식 코드Conformal Prediction for Causal Effects of Continuous Treatments
https://github.com/mad-stat/EGDL
공식 코드Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak
https://github.com/maozj6/hsai-predictor
공식 코드https://github.com/matinmoezzi/ups_conformal_classification
공식 코드An Uncertainty-Aware Pseudo-Label Selection Framework using Regularized Conformal Prediction
https://github.com/matteogaspa/EffCrossCP
공식 코드Improving the statistical efficiency of cross-conformal prediction
https://github.com/matteogaspa/coma
공식 코드https://github.com/matthewyccheung/conformal-metric
공식 코드Metric-Guided Conformal Bounds for Probabilistic Image Reconstruction
https://github.com/maxineyu/codes_symmpi
공식 코드https://github.com/mayo-radiology-informatics-lab/conflare
공식 코드https://github.com/meshiba/robust-conformal-od
공식 코드Robust Conformal Outlier Detection under Contaminated Reference Data
https://github.com/meshiba/sppi
공식 코드https://github.com/ml-jku/hopcpt
공식 코드Conformal Prediction for Time Series with Modern Hopfield Networks
https://github.com/ml-postech/selective-generation
공식 코드https://github.com/ml-stat-Sustech/Parametric-Scaling-Law-CP-Tuning
공식 코드Parametric Scaling Law of Tuning Bias in Conformal Prediction
https://github.com/ml-stat-Sustech/conformal_prediction_via_label_ranking
공식 코드https://github.com/ml-stat-sustech/torchcp
공식 코드https://github.com/mli-lab/recalibrating_conformal_prediction
공식 코드Test-time Recalibration of Conformal Predictors Under Distribution Shift Based on Unlabeled Examples
https://github.com/msesia/chr
공식 코드https://github.com/msesia/conformal-label-noise
공식 코드https://github.com/mshoush/rl-prescriptive-monitoring
공식 코드Prescriptive Process Monitoring Under Resource Constraints: A Reinforcement Learning Approach
https://github.com/mufangying/informativeness-of-wcp
공식 코드https://github.com/mzaffran/adaptiveconformalpredictionstimeseries
공식 코드https://github.com/mzaffran/conformalpredictionmissingvalues
공식 코드https://github.com/n4feng/ResponseQualityAssessment
공식 코드Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.